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Intelligent fault diagnosis based on multi-source information fusion and attention-enhanced networks
Abstract Deep learning has been widely applied in the field of intelligent fault diagnosis, achieving remarkable progress in feature extraction and classification performance. However, most existing methods still face challenges in simultaneously capturing the temporal information and global features during the bearing operation process, which leads to insufficient acquisition of fault-related information. Moreover, under complex and harsh working environments, single-source fault diagnosis methods often struggle to stably extract fault features. To address these issues, this paper proposes an intelligent fault diagnosis method based on multi-source information fusion, aiming to enhance stability through the extraction and integration of rich feature representations. Specifically, vibration and current signals are transformed from raw time-domain data into time-frequency representations using continuous wavelet transform. At the image level, a grayscale-weighted fusion strategy is employed to effectively integrate multi-source information. In terms of model design, a diagnostic framework combining convolutional neural networks with attention mechanisms is constructed, enabling effective capture of both temporal information and global feature dependencies of bearing faults. Experimental results on a publicly available bearing fault dataset demonstrate that the proposed method consistently outperforms existing single-source and multi-source diagnosis models across various evaluation metrics, achieving higher fault recognition accuracy.
Pre-trained ChatGPT for report generation in automated microbial identification and antibiotic susceptibility testing systems
Medicine Nobel goes to scientists who revealed secrets of immune system ‘regulation’
Effects of manure application on paddy soil phosphorus in China based on a meta-analysis
Arithmetic and reading skills mediate the link between math and reading anxiety and word problem solving
Mitigating urban rainstorm waterlogging disasters in China through enhanced vegetation coverage and sponge city construction
Creative hobbies could slow brain ageing at the molecular level
Revealing synchrony in pea plants using wavelet coherence analysis
Abstract In this study, we apply Wavelet Transform Coherence (WTC) analysis—a time–frequency method commonly used in human and animal synchrony research—to examine whether co-potted pea plant dyads exhibit synchronized movement during tendril approach to intertwine. This behaviour allows plants to form braided structures, providing mutual support in the absence of external scaffolds. The results reveal significant coherence, particularly pronounced at the beginning and at the end of the movement sequence. However, this effect varies across dyads, displaying a certain degree of heterogeneity in the coherence patterns. Overall, the analyses indicate that plant movements are temporally structured and non-random; nonetheless, the substantial inter-dyad variability prevents this outcome from being generalized unequivocally. We propose that such synchrony may emerge from embodied mechanisms, including mechanical feedback and chemical signalling. This work extends the application of WTC analysis to plant systems and challenges the assumption that complex coordination requires neural substrates, highlighting the role of distributed, non-neural processes in facilitating cooperative behaviour among living organisms.
A pan-cancer analysis of the oncogenic and immunological roles of THOC3 in human cancer
Correction: In vitro dual (anticancer and antiviral) activity of the carotenoids produced by haloalkaliphilic archaeon Natrialba sp. M6
Bone regeneration induced by a novel quercetin/a-CSH/n-HA composite in critical size tibia defect of rats with osteoporosis
Uncovering the anti-cervical cancer mechanism of Ziyuglycoside I via integrated network pharmacology molecular docking and experimental validation
‘Rogue’ planet is fastest-growing ever observed
Targeted hip abductor fatigue alters trunk and lower limb biomechanics during Single-Leg landing
Abstract Fatigue of the hip abductor muscles may influence lower limb biomechanics and potentially contribute to anterior cruciate ligament (ACL) injury risk. However, the effects of targeted hip abductor fatigue on trunk, pelvis and lower limb coordination during landing tasks remain unclear. The present study aimed to investigate how targeted hip abductor fatigue alters the biomechanics of the trunk, pelvis, and lower extremity during single-leg landing (SLL). Twenty healthy male recreational athletes performed SLL before and after a targeted hip abductor fatigue protocol. Kinematic and kinetic data were collected using a three-dimensional motion capture system and force plates, with analysis focused on the timing of peak vertical ground reaction force. Following fatigue, participants exhibited increased hip abduction angle and trunk right inclination, as well as decreased hip flexion and external hip abduction moment. Notably, the external knee abduction moment significantly increased post-fatigue, though it remained negative in absolute value. Increased pelvic left rotation was also observed, indicating compensatory adjustments in trunk-pelvis coordination. These adaptations indicate that targeted muscle fatigue induces complex biomechanical responses across the kinetic chain, rather than uniformly increasing injury risk through valgus-prone mechanics. While the observed changes may reflect stabilizing strategies under fatigue, their implications for ACL loading require further clarification. The current study highlights the relevance of considering whole-body biomechanical responses to targeted fatigue and contributes to a more detailed understanding of neuromuscular control during landing. These findings may support the refinement of injury prevention approaches that address segmental coordination under fatigued conditions.
Marcus kinetics control singlet and triplet oxygen evolving from superoxide
Abstract Oxygen redox chemistry is central to life1 and many human-made technologies, such as in energy storage2–4. The large energy gain from oxygen redox reactions is often connected with the occurrence of harmful reactive oxygen species3,5,6. Key species are superoxide and the highly reactive singlet oxygen3–7, which may evolve from superoxide. However, the factors determining the formation of singlet oxygen, rather than the relatively unreactive triplet oxygen, are unknown. Here we report that the release of triplet or singlet oxygen is governed by individual Marcus normal and inverted region behaviour. We found that as the driving force for the reaction increases, the initially dominant evolution of triplet oxygen slows down, and singlet oxygen evolution becomes predominant with higher maximum kinetics. This behaviour also applies to the widely observed superoxide disproportionation, in which one superoxide is oxidized by another, in both non-aqueous and aqueous systems, with Lewis and Brønsted acidity controlling the driving forces. Singlet oxygen yields governed by these conditions are relevant, for example, in batteries or cellular organelles in which superoxide forms. Our findings suggest ways to understand and control spin states and kinetics in oxygen redox chemistry, with implications for fields, including life sciences, pure chemistry and energy storage.