Wiley最新文献

Model predictive control has recently attracted the attention of researchers in control of permanent magnet synchronous motor drives due to advantages such as simple concepts and fast dynamics. However, it is highly sensitive to changes in motor parameters and unmodelled uncertainties. To solve this problem, a model-free predictive control based on an ultra-local model is proposed in this paper, which uses only the input and output of the system based on nominal parameters. To enhance the drive performance and simplification of implementation, current control, and speed control are performed simultaneously based on the optimization of a cost function without using any PI speed or PI current controller. In the proposed method named ‛model-free predictive current and speed control′ (MFPCSC), to reduce the sensitivity to model parameters and uncertainties, a nonlinear disturbance observer (NDO) is used, which accurately estimates all uncertainties and the effect of parameters’ change. The proposed MFPCSC-NDO control method has good behaviour in tracking the speed and current reference values and has high robustness to parameter changes. The performance of the proposed method is compared with two methods of model-based predictive current control and model-free predictive current control by simulation and its behaviour is confirmed with experimental results.

Existing click-based interactive image segmentation methods typically initiate object extraction with the first click and iteratively refine the coarse segmentation through subsequent interactions. Unlike box-based methods, click-based approaches mitigate ambiguity when multiple targets are present within a single bounding box, but suffer from a lack of precise location and outline information. Inspired by instance segmentation, the authors propose a Generated-bbox Guided method that provides location and outline information using an automatically generated bounding box, rather than a manually labelled one, minimising the need for extensive user interaction. Building on the success of vision transformers, the authors adopt them as the network architecture to enhance model's performance. A click-based interactive image segmentation network named the Generated-bbox Guided Coarse-to-Fine Network (GCFN) was proposed. GCFN is a two-stage cascade network comprising two sub-networks: Coarsenet and Finenet. A transformer-based Box Detector was introduced to generate an initial bounding box from a inside click, that can provide location and outline information. Additionally, two feature enhancement modules guided by foreground and background information: the Foreground-Background Feature Enhancement Module (FFEM) and the Pixel Enhancement Module (PEM) were designed. The authors evaluate the GCFN method on five popular benchmark datasets and demonstrate the generalisation capability on three medical image datasets.

Bamboo's susceptibility to mildew leads to contamination and economic losses, underscoring the need for effective prevention methods. This study investigated the impregnation of bamboo with ionic liquids, specifically optimizing the pressurized process of dodecylpyridinium chloride, while evaluating treatment effectiveness and leaching resistance. Techniques such as Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), energy-dispersive spectroscopy (EDS), and ultraviolet–visible spectroscopy (UV) were employed to analyze the distribution and bonding of dodecylpyridinium chloride within the bamboo. The optimized impregnation parameters were determined to be a concentration of 6.88 mg/mL, a duration of 98 min, and a pressure of 0.61 MPa. Treated bamboo exhibited excellent antibacterial properties and leaching resistance, achieving 100% efficacy against bamboo mildew. Furthermore, after 14 days of soaking, the retention of dodecylpyridinium chloride decreased by only 27.3%. This study highlights a sustainable method for mildew prevention, which is crucial for enhancing the durability and utility of bamboo products.

Hyperspectral images usually lie on low-dimensional nonlinear manifolds, leading to a challenging clustering task. Deep subspace clustering–based methods have been successful in this task by converting features to linear embedding using an auto-encoder with $�{\ell }_2$ norm. In this setting, the embedding of the auto-encoder just learns the implicit geometric structure of original samples and loses its distribution. However, the sample distribution alignment is a generalisation of sample alignment. To remedy these issues, in this article, we propose a promising method, named DSCOT, for improving subspace clustering. Specifically, we measure the reconstruction error of the auto-encoder leveraging optimal transport distance that explicitly embeds geometric distance between samples and preserves embedding distribution in observation space. It results in more appropriate embedding for subspace clustering. Several experiments on three widely used databases show that the proposed method is superior to most state-of-the-art methods.

The aim of this study was to evaluate the influence of burdock fructooligosaccharide (BFO) treatment on postharvest blueberries, specifically focusing on the influence of membrane lipid metabolism on overall quality. Our findings revealed that BFO treatment effectively suppressed decay index and preserved firmness in blueberry fruit. At the same time, BFO treatment effectively mitigated the production of H₂O₂ and malondialdehyde (MDA), while reinforcing the activities of antioxidant enzymes and enhancing the expression level. Moreover, BFO treatment preserved high amounts of unsaturated fatty acids while suppressing the gene expression and enzyme activity of phospholipase D (PLD), lipase, and lipoxygenase (LOX). In summary, the application of BFO effectively retards the metabolism of membrane lipids and preserves the integrity of cell membranes, thereby delaying blueberry senescence.

Mycobacterium kansasii (Mkan) is a nontuberculous mycobacterium (NTM) commonly found in aquatic environments and is responsible for chronic pulmonary infections resembling tuberculosis. Treatment requires multiple antibiotics for at least 12 months, highlighting the challenge in managing Mkan infections. In this study, 50 thiourea derivatives were synthesized and evaluated for their cytotoxic and inhibitory effects on bacterial growth in culture and in infected macrophages using Mkan strains with varying virulence levels. In silico studies explored the structure–activity relationship (SAR) and the pharmacokinetic and toxicological profiles of the most active thiourea derivatives. As a result, 15 derivatives showed promising inhibitory activity against the reference strain, Mkan 12478. Of these, derivatives 2, 47, and 49 also significantly inhibited clinical isolates 10953 and 8835 without displaying cytotoxic effects. Furthermore, these three derivatives could inhibit intracellular mycobacterial growth in RAW 264.7 macrophages infected with strains 12478 or 8835. SAR studies revealed molecular volume and polar surface (PSA) area as important features for these thiourea derivatives, directly correlating with their antimycobacterial profile. In silico studies indicated that these compounds are potentially suitable for oral administration and have less toxicological effects than rifampicin, providing a safer alternative for antimycobacterial treatment. In conclusion, our findings suggest that thiourea derivatives 2, 47, and 49 are promising antimycobacterial agents for treating infections caused by Mkan.

Potassium periodate (KIO₄) catalyzed novel, efficient and highly regioselective one-pot synthesis of substituted benzimidazoles has been carried out in good to excellent yields via condensation–cyclisation reactions involving a variety of aldehydes and o-phenylenediamines. As a catalyst, KIO₄ shows good compatibility with various substrates, easy removal, easy handling, operational simplicity, and work in mild reaction conditions. A comparative study, microwave (MW) versus conventional method, for synthesizing 2-substituted benzimidazoles via KIO₄ catalysis is also described. It was observed that the microwave irradiation approach improves the yield and minimizes time (from hour to min), and represents more advantageous eco-friendly quicker chemistry.