Zero-Shot Fault Diagnosis for Smart Process Manufacturing via Tensor Prototype Alignment.

Identifying unseen faults is a crux of the digital transformation of process manufacturing. The ever-changing manufacturing process requires preset models to cope with unseen problems. However, most current works focus on recognizing objects seen during the training phase. Conventional zero-shot recognition methods perform poorly when they are applied directly to these tasks due to the different scenarios and limited generalizability. This article yields a tensor-based zero-shot fault diagnosis framework, termed MetaEvolver, which is dedicated to improving fault diagnosis accuracy and unseen domain generalizability for practical process manufacturing scenarios. MetaEvolver learns to evolve the dual prototype distributions for each uncertain meta-domain from seen faults and then adapt to unseen faults. We first propose the concept of the uncertain meta-domain and then construct corresponding sample prototypes with the guidance of class-level attributes, which produce the sample-attribute alignment at the prototype level. MetaEvolver further collaboratively evolves the uncertain meta-domain dual prototypes by injecting the prototype distribution information of another modality, boosting the sample-attribute alignment at the distribution level. Building on the uncertain meta-domain strategy, MetaEvolver is prone to achieving knowledge transferring and unseen domain generalization with the optimization of several devised loss functions. Comprehensive experimental results on five process manufacturing data groups and five zero-shot benchmarks demonstrate that our MetaEvolver has great superiority and potential to tackle zero-shot fault diagnosis for smart process manufacturing.

Tensor-Empowered Adaptive Learning for Few-Shot Streaming Tasks.

Various stream learning methods are emerging in an endless stream to provide a wealth of solutions for artificial intelligence in streaming data scenarios. However, when each data stream is oriented to a different target space, it forces stream learning approaches oriented to the same task to be no longer applicable. Due to inconsistent target spaces for different tasks, the previous approaches fail on the new streaming tasks or it is impracticable to be trained from scratch with few labeled samples at the beginning. To this end, we have proposed an adaptive learning scheme for few-shot streaming tasks with the contributions of tensor and meta-learning. This adaptive scheme is conducive to mitigating the domain shift when a new task has few labeled samples. We elaborate a novel tensor-empowered attention mechanism derived from nonlocal neural networks, which enables to capture long-range dependency and preserve the high-dimensional structure to refine the global features of streaming tasks. Furthermore, we develop a fine-grained similarity computing approach, which is prone to better characterize the difference across few-shot streaming tasks. To show the superiority of our method, we have carried out extensive experiments on three popular few-shot datasets to simulate streaming tasks and evaluate the performance of adaptation. The results show that our proposed method has achieved competitive performance for few-shot streaming tasks compared with the state-of-the-art (SOTA).

Resveratrol attenuates pulmonary embolism associated cardiac injury by suppressing activation of the inflammasome via the MALAT1­miR­22­3p signaling pathway.

Resveratrol (RS) has been reported to prevent the development of cardiac injury induced by pulmonary embolism (PE). The present study aimed to explore the potential mechanism of RS involved in cardiac injury induced by PE. A luciferase assay was conducted to detect the effect of RS on promoter efficiency of metastasis associated lung adenocarcinoma transcript 1 (MALAT1), in­silico analysis and luciferase assays were performed to explore the regulatory relationship between MALAT1, microRNA (miR)­22­3p and NLRP3. Reverse transcription PCR, western blot analysis and ELISA were carried out to examine MALAT1, miR­22­3p, NLRP3, ASC, Caspase­1, interleukin (IL)­1ß and IL­18 among different animal model groups, including the sham group, PE associated cardiac injury group and PE associated cardiac injury plus RS group. The results revealed that RS downregulated promoter efficiency of MALAT1 and MALAT1 directly targeted miR­22­3p, and luciferase activity of MALAT1 was inhibited by miR­22­3p, and furthermore miR­22­3p inhibited the expression of NLRP3 by binding to complementary sequences in the 3' untranslated region of NLRP3. MALAT1, NLRP3, ASC, Caspase­1, IL­1ß and IL­18 levels were much increased, while miR­22­3p level was much decreased in PE associated cardiac injury group compared with the sham group, while the RS upon the PE associated cardiac injury group slightly reduced the upregulated MALAT1/NLRP3 level and elevated the downregulated miR­22­3p level. In conclusion, it was demonstrated that RS has been demonstrated to prevent the development of cardiac injury induced by PE via modulating the expression of MALAT1 and further affect miR­22­3p and NLRP3.

Lack of association between the 389C>T polymorphism (rs769217) in the catalase (CAT) gene and the risk of vitiligo: an update by meta-analysis.

BACKGROUND/OBJECTIVES: The catalase (CAT) T/C at codon 389 in the exon 9 polymorphism has been implicated in susceptibility to vitiligo but a large number of studies have reported inconclusive results. The purpose of this study is to evaluate the association between the catalase gene polymorphism (389C>T) and the risk of vitiligo. METHODS: A meta-analysis was carried out to analyse the association between 389C>T and vitiligo risk. RESULTS: Eight case-control studies with 2923 cases and 4237 controls were included in the meta-analysis. The results indicated that there was no association between this polymorphism and vitiligo (TT + CT versus CC: OR = 1.08, 95% CI = 0.98-1.20, P = 0.11, T versus C: OR = 1.07, 95% CI = 0.99-1.16, P = 0.092). In a subgroup analysis by ethnicity, no significant association between the CAT gene 389C>T polymorphism and vitiligo susceptibility was found in Caucasians (TT + CT versus CC: OR = 1.15, 95% CI = 0.98-1.35, P = 0.08; T versus C: OR = 1.07, 95% CI = 0.97-1.19, P = 0.173) and Asians (TT + CT versus CC: OR = 1.12, 95% CI =0.93-1.34, P = 0.23; T versus C: OR = 1.07, 95% CI = 0.94-1.21, P = 0.321). CONCLUSIONS: Our results suggest that 389C>T may not contribute to vitiligo susceptibility. However, larger primary studies with the consideration of gene-environment and gene-gene interactions are still required to further evaluate the interaction of CAT gene polymorphism with vitiligo susceptibility.