A Survey on Unsupervised Anomaly Detection Algorithms for Industrial Images

In line with the development of Industry 4.0, surface defect detection/anomaly detection becomes a topical subject in the industry field. Improving efficiency as well as saving labor costs has steadily become a matter of great concern in practice, where deep learning-based algorithms perform better than traditional vision inspection methods in recent years. While existing deep learning-based algorithms are biased towards supervised learning, which not only necessitates a huge amount of labeled data and human labor, but also brings about inefficiency and limitations. In contrast, recent research shows that unsupervised learning has great potential in tackling the above disadvantages for visual industrial anomaly detection. In this survey, we summarize current challenges and provide a thorough overview of recently proposed unsupervised algorithms for visual industrial anomaly detection covering five categories, whose innovation points and frameworks are described in detail. Meanwhile, publicly available datasets for industrial anomaly detection are introduced. By comparing different classes of methods, the advantages and disadvantages of anomaly detection algorithms are summarized. Based on the current research framework, we point out the core issue that remains to be resolved and provide further improvement directions. Meanwhile, based on the latest technological trends, we offer insights into future research directions. It is expected to assist both the research community and industry in developing a broader and cross-domain perspective

Application-Driven AI Paradigm for Human Action Recognition

Human action recognition in computer vision has been widely studied in recent years. However, most algorithms consider only certain action specially with even high computational cost. That is not suitable for practical applications with multiple actions to be identified with low computational cost. To meet various application scenarios, this paper presents a unified human action recognition framework composed of two modules, i.e., multi-form human detection and corresponding action classification. Among them, an open-source dataset is constructed to train a multi-form human detection model that distinguishes a human being's whole body, upper body or part body, and the followed action classification model is adopted to recognize such action as falling, sleeping or on-duty, etc. Some experimental results show that the unified framework is effective for various application scenarios. It is expected to be a new application-driven AI paradigm for human action recognition

Several Critical Cell Types, Tissues, and Pathways Are Implicated in Genome-Wide Association Studies for Systemic Lupus Erythematosus

We aimed to elucidate the cell types, tissues, and pathways influenced by common variants in systemic lupus erythematosus (SLE). We applied a nonparameter enrichment statistical approach, termed SNPsea, in 181 single nucleotide polymorphisms (SNPs) that have been identified to be associated with the risk of SLE through genome-wide association studies (GWAS) in Eastern Asian and Caucasian populations, to manipulate the critical cell types, tissues, and pathways. In the two most significant cells’ findings (B lymphocytes and CD14+ monocytes), we subjected the GWAS association evidence in the Han Chinese population to an enrichment test of expression quantitative trait locus (QTL) sites and DNase I hypersensitivity, respectively. In both Eastern Asian and Caucasian populations, we observed that the expression level of SLE GWAS implicated genes was significantly elevated in xeroderma pigentosum B cells (P ≤ 1.00 × 10−6), CD14+ monocytes (P ≤ 2.74 × 10−4) and CD19+ B cells (P ≤ 2.00 × 10−6), and plasmacytoid dendritic cells (pDCs) (P ≤ 9.00 × 10−6). We revealed that the SLE GWAS-associated variants were more likely to reside in expression QTL in B lymphocytes (q1/q0 = 2.15, P = 1.23 × 10−44) and DNase I hypersensitivity sites (DHSs) in CD14+ monocytes (q1/q0 = 1.41, P = 0.08). We observed the common variants affected the risk of SLE mostly through by regulating multiple immune system processes and immune response signaling. This study sheds light on several immune cells and responses, as well as the regulatory effect of common variants in the pathogenesis of SLE

Potential Tumor Suppressor NESG1 as an Unfavorable Prognosis Factor in Nasopharyngeal Carcinoma

BACKGROUND:Recently we identified nasopharyngeal epithelium specific protein 1 (NESG1) as a potential tumor suppressor in nasopharyngeal carcinoma (NPC). The purpose of this study is to investigate the involvement of NESG1 in tumor progression and prognosis of human NPC. METHODOLOGY/PRINCIPAL FINDINGS:NESG1 protein expression in NPC was examined. Survival analysis was performed using Kaplan-Meier method. The effect of NESG1 on cell proliferation, migration, and invasion were also investigated. RESULTS:NESG1 expression was downregulated in atypical hyperplasia and NPC samples compared to normal and squamous nasopharynx tissues. Reduced protein expression was negatively associated with the status of NPC progression. Patients with lower NESG1 expression had a shorter overall survival and disease-free time than did patients with higher NESG1 expression. Multivariate analysis suggested NESG1 expression as an independent prognostic indicator for NPC patient survival. Proliferation, migration, and invasion ability were significantly increased in cell lines following lentiviral-mediated shRNA suppression of NESG1 expression. Microarray analysis indicated that NESG1 participated in multiple pathways, including MAPK signaling and cell cycle regulation. Finally, DNA methylation microarray examination revealed a lack of hypermethylation at the NESG1 promoter, suggesting other mechanisms are involved in suppressing NESG1 expression in NPC. CONCLUSION:Our studies are the first to demonstrate that decreased NESG1 expression is an unfavorable prognostic factor for NPC

Review of reliability analysis methods for performance degradation of aircraft lock mechanism

With the rapid development of aerospace equipment,the reliability requirements of military equipment are gradually increasing,and the reliability of the aircraft lock mechanism is crucial to the safety of aircraft take-off and landing. In this paper,the aircraft cabin door lock mechanism is taken as the research object. Firstly,a large number of cabin door lock mechanisms are investigated through literature and the characteristics and failure modes of the lock mechanism are analyzed,and the working principle of the lock mechanism is described. Secondly,the failure mechanism modeling of lock mechanism and the status quo of gradual damage of lock mechanism and the existing problems are described. The reliability research status of locking mechanism at home and abroad is analyzed.The reliability analysis of multi-link mechanism and lock mechanism are classified and combed. Finally,the research ideas of reliability analysis of locking mechanism are summarized,the existing problems and research trends of reliability analysis of complex mechanisms are also prospected

The Method of Axial Drift Compensation of Laser Differential Confocal Microscopy Based on Zero-tracking

Laser differential confocal microscopy (DCM) has advantages of high axial resolution and strong ability of focus identification. However, the imaging mechanism of point scanning needs long measurement time, in the process due to itself mechanical instability and the influence of environment vibration the axial drift of object position is inevitable, which will reduce lateral resolution of the DCM. To ensure the lateral resolution we propose an axial drift compensation method based on zero-tracking in this paper. The method takes advantage of the linear region of differential confocal axial response curve, gets axial drift by detecting the laser intensity; uses grating sensor to monitor the real-time axial drift of lifting stage and realizes closed-loop control; uses capacitive sensor of objective driver to measure its position. After getting the axial drift of object, the lifting stage and objective driver will be driven to compensate position according to the axial drift. This method is realized by using Visual Studio 2010, and the experiment demonstrates that the compensation precision of the proposed method can reach 6 nm. It is not only easy to implement, but also can compensate the axial drift actively and real-timely. Above all, this method improves the system stability of DCM effectively

Acteoside Derived from Cistanche Improves Glucocorticoid-Induced Osteoporosis by Activating PI3K/AKT/mTOR Pathway

Objective Glucocorticoids are widely used in clinical practice; however, they can cause side effects, such as osteoporosis. Acteoside (ACT) from Cistanche has been used to combat a variety of diseases. The study was conducted to evaluate the efficacy of ACT in glucocorticoid-induced osteoporosis (GIOP) and its potential mechanism. Methods Dexamethasone (Dex) was injected intramuscularly to induce osteoporosis in a rat model, and ACT was given orally. ACT was supplemented in vivo in Dex-stimulated osteoblastic MC3T3-E1 cells. RT-qPCR was performed to assess the mRNA levels of bone formation (Runx2, CoL1A1), and bone resorption (OPG and RANKL). A commercial ELISA kit was applied to assess serum OC and CTX levels. Western blot was performed to assess protein levels in the PI3K/AKT/mTOR signaling pathway. CCK-8 assay and flow cytometry were performed to assess osteoblast viability and apoptosis. Results ACT reduced Dex-induced bone microstructure deterioration, increased serum levels of OC, and decreased the levels of CTX (P < 0.05). In the MC3T3-E1 cells, Dex inhibited cell viability and promoted apoptosis; however, this effect was greatly attenuated by ACT (P < 0.05). Concurrently, ACT reversed the reduction in Runx2, osterix, CoL1A1, and OPG mRNA levels, ALP activity, and the promotion of RANKL by Dex. Additionally, ACT attenuated Dex-induced inhibition of p-AKT/AKT, p-mTOR/mTOR, and p-PI3K/PI3K protein levels by Dex (P < 0.05), while the PI3K/AKT/mTOR pathway inhibitor LY294002 diminished the potential effect of ACT (P < 0.05). Conclusion ACT from Cistanche may exert osteoprotective effects by activating the PI3K/AKT/mTOR signaling pathway to alleviate Dex-induced osteoporosis

Detection of Subsurface Damage Morphology of Lapped Optical Components by Analysis of the Fluorescence Lifetimes of Quantum Dots

Optical components inevitably suffer subsurface damage (SSD) during grinding and lapping, and this SSD substantially degrades the performance of optical systems. Moreover, given the surface roughness of optical components after grinding or lapping, it is impossible to non-destructively and accurately detect SSD generated by these processes, especially regarding the morphological details of such SSD. Accordingly, a novel method for detecting the morphological details of SSD in lapped optical components via analysis of the fluorescence lifetimes of quantum dots (QDs) is developed. This paper shows that, (1) compared with other methods, this novel method detects more morphological details of SSD in lapped optical components and that this detection is unaffected by the elemental composition/size/fluorescence lifetime of the QDs; (2) SSD detection achieved by analyzing the QD fluorescence lifetime can detect more SSD details on the premise of achieving the detection of SSD distribution and depth; and (3) the SSD in lapped optical components exhibits textural features, and “hole”-type SSD is detected in addition to “solid”-point and strip SSD. These findings will facilitate research on the formation mechanism of SSD, thereby enabling improvements in optical manufacturing techniques