Functional control structure model for the complex systems and its application in system safety analysis

The safety problem for the complex system is regarded as a control problem other than probability one, where the overall functional control structure model of the complex system could be configured in terms of the relationships among their functional labels. The hazards are due to the unsafe control actions (UCA), or the malfunctional control action (MCA). Meanwhile, UCA and MCA are due to the error feedback information (EFI), the error environment variables (EEV), the error state variables (ESE), the error command inputs (ECI), the error working modes (EWM), and the error process models (EPM), etc. Every function or component would be described as 10 labels, which are the input command (IC), the feedback to the upper level (FU), the control action (CA), the feedback from the lower levels (FL), the external input command (EC), the process model (PM), other related state variable (SV), the precondition (PC), the resource and the executing condition (RE) of the system, and the environment variable (EV). The aircraft wheel brake system’s control structure model is given to show its effectiveness

FoveaBox: Beyond Anchor-based Object Detector

We present FoveaBox, an accurate, flexible, and completely anchor-free framework for object detection. While almost all state-of-the-art object detectors utilize predefined anchors to enumerate possible locations, scales and aspect ratios for the search of the objects, their performance and generalization ability are also limited to the design of anchors. Instead, FoveaBox directly learns the object existing possibility and the bounding box coordinates without anchor reference. This is achieved by: (a) predicting category-sensitive semantic maps for the object existing possibility, and (b) producing category-agnostic bounding box for each position that potentially contains an object. The scales of target boxes are naturally associated with feature pyramid representations. In FoveaBox, an instance is assigned to adjacent feature levels to make the model more accurate.We demonstrate its effectiveness on standard benchmarks and report extensive experimental analysis. Without bells and whistles, FoveaBox achieves state-of-the-art single model performance on the standard COCO and Pascal VOC object detection benchmark. More importantly, FoveaBox avoids all computation and hyper-parameters related to anchor boxes, which are often sensitive to the final detection performance. We believe the simple and effective approach will serve as a solid baseline and help ease future research for object detection. The code has been made publicly available at https://github.com/taokong/FoveaBox .Comment: IEEE Transactions on Image Processing, code at: https://github.com/taokong/FoveaBo

Named Entity Recognition in Chinese Clinical Text

Objective: Named entity recognition (NER) is one of the fundamental tasks in natural language processing (NLP). In the medical domain, there have been a number of studies on NER in English clinical notes; however, very limited NER research has been done on clinical notes written in Chinese. The goal of this study is to develop corpora, methods, and systems for NER in Chinese clinical text. Materials and methods: To study entities in Chinese clinical text, we started with building annotated clinical corpora in Chinese. We developed an NER annotation guideline in Chinese by extending the one used in the 2010 i2b2 NLP challenge. We randomly selected 400 admission notes and 400 discharge summaries from Peking Union Medical College Hospital (PUMCH) in China. For each note, four types of entities including clinical problems, procedures, labs, and medications were annotated according to the developed guideline. In addition, an annotation tool was developed to assist two MD students to annotate Chinese clinical documents. A comparison of entity distribution between Chinese and English clinical notes (646 English and 400 Chinese discharge summaries) was performed using the annotated corpora, to identify the important features for NER. In the NER study, two-thirds of the 400 notes were used for training the NER systems and one-third were used for testing. We investigated the effects of different types of features including bag-of-characters, word segmentation, part-of-speech, and section information, with different machine learning (ML) algorithms including Conditional Random Fields (CRF), Support Vector Machines (SVM), Maximum Entropy (ME), and Structural Support Vector Machines (SSVM) on the Chinese clinical NER task. All classifiers were trained on the training dataset, evaluated on the test set, and microaveraged precision, recall, and F-measure were reported. Results: Our evaluation on the independent test set showed that most types of features were beneficial to Chinese NER systems, although the improvements were limited. By combining word segmentation and section information, the system achieved the highest performance, indicating that these two types of features are complementary to each other. When the same types of optimized features were used, CRF and SSVM outperformed SVM and ME. More specifically, SSVM reached the highest performance among the four algorithms, with F-measures of 93.51% and 90.01% for admission notes and discharge summaries respectively. Conclusions: In this study, we created large annotated datasets of Chinese admission notes and discharge summaries and then systematically evaluated different types of features (e.g., syntactic, semantic, and segmentation information) and four ML algorithms including CRF, SVM, SSVM, and ME for clinical NER in Chinese. To the best of our knowledge, this is one of the earliest comprehensive effort in Chinese clinical NER research and we believe it will provide valuable insights to NLP research in Chinese clinical text. Our results suggest that both word segmentation and section information improves NER in Chinese clinical text, and SSVM, a recent sequential labelling algorithm, outperformed CRF and other classification algorithms. Our best system achieved F-measures of 90.01% and 93.52% on Chinese discharge summaries and admission notes, respectively, indicating a promising start on Chinese NLP research

A comparison of electronic health records at two major Peking University Hospitals in China to United States meaningful use objectives

BACKGROUND: In accordance with the People’s Republic of China’s (China) National Health Reform Plan of 2009, two of the nation’s leading hospitals, located in Beijing, have implemented electronic medical record (EMR) systems from different vendors. To inform future EMR adoption and policy in China, as well as informatics research in the US, this study compared the United State’s Hospital Meaningful Use (MU) Objectives (phase 1) objectives to the EMR functionality of two early hospital EMR adopters in China. METHODS: At both hospitals, the researchers observed a physician using the EMR and noted MU functionality that was seen and functionality that was not seen yet was available in the EMR. The information technology department was asked about the availability of functionality neither observed nor known to the physician. RESULTS AND CONCLUSIONS: Approximately half the MU objectives were available in each EMR. Some differences between the EMRs in the study and MU objectives were attributed to operational differences between the health systems and the cultures in the two countries

Global research trends in benign paroxysmal positional vertigo: a bibliometric analysis

BackgroundBenign paroxysmal positional vertigo is the most common disease in which vertigo is the main clinical manifestation, and it has become a global medical problem, affecting a wide range of areas and seriously affecting the quality of human life.ObjectiveThis article presents an analysis of the current characteristics of BPPV-related research and summarizes the current hot topics and trends, with the goal of inspiring future research into the prevention and treatment of BPPV, thereby improving the differential diagnosis and prevention of peripheral vertigo.MethodsA bibliometric approach was used to collect 1,219 eligible studies on BPPV from four databases—PubMed, Embase, Scopus, and Web of Science—published between 1974 and 2022. The characteristics and status of the accumulated scientific output were processed using R and VOSviewer so that we could visualize any trends or hotspots.ResultsThe results showed a significant increase in the annual number of publications, with an average annual growth rate of 21.58%. A possible reason for the especially pronounced peak in 2021 was an increase in the prevalence of BPPV as a result of COVID-19. The new coronavirus became a focus of research in 2021. A total of 3,876 authors (of whom 1,097 were first authors) published articles in 307 different journals; 15.7% of the articles were published in Acta Oto-Larygologica, Otology and Neurotology, and Frontiers in Neurology. Acta Oto-Laryngologica was well ahead of the other journals in terms of growth rate and number of articles published. American scholars generated the largest number of articles overall, and the USA was involved in the greatest number of international collaborations, followed by Italy and China. The themes of the research centered around three topics, namely the treatment of BPPV, its influencing factors, and diagnosis.ConclusionsThere has been a major increase in BPPV-related research over the last 50 years, leading to an increase in related articles and rapid development of the field. Key directions for future research include the improvement of individualized treatment for residual symptoms after initial treatment of BPPV among the elderly; effective control of comorbidities such as osteoporosis; and secondary inner ear disease, such as Ménière's disease

Enhanced corrosion and wear resistance properties of carbon fiber reinforced Ni-based composite coating by laser cladding

To enhance the wear resistance and corrosion resistance of Ni-based coatings, carbon fibers reinforced nickel-based composite coatings (CFs/Ni) were fabricated on the surface of 1Cr13 stainless steel by laser cladding (LC). The microstructure characteristics, microhardness, wear and corrosion performances of the composite coatings were investigated. The results show that CFs can effectively improve the corrosion and wear resistances of Ni-based coatings. With increasing laser scanning speed, the morphology of CFs in composite coatings is more integral and the corrosion and wear resistances of the composite coatings are improved. Especially, when laser scanning speed is increased to 8 mm/s, the average microhardness of the composite coating reaches up to 405 HV0.2, which is about 1.3 times higher than that of Ni-based coating. Moreover, the corrosion current density and the wear rate of the composite coating are only 7% and 55% of those of the Ni-based coating, respectively, which is attributed to the good properties and homogeneous distribution of CFs and finer microstructure of composite coating

DNA Methylation and miRNA-1296 Act in Concert to Mediate Spatiotemporal Expression of KPNA7 During Bovine Oocyte and Early Embryonic Development

Abstract Background: Epigenetic regulation of oocyte-specific maternal factors is essential for oocyte and early embryonic development. KPNA7 is an oocyte-specific maternal factor, which controls transportation of nuclear proteins important for early embryonic development. To elucidate the epigenetic mechanisms involved in the controlled expression of KPNA7, both DNA methylation associated transcriptional silencing and microRNA (miRNA)-mediated mRNA degradation of KPNA7 were examined. Results: Comparison of DNA methylation profiles at the proximal promoter of KPNA7 gene between oocyte and 6 different somatic tissues identified 3 oocyte-specific differentially methylated CpG sites. Expression of KPNA7 mRNA was reintroduced in bovine kidney-derived CCL2 cells after treatment with the methylation inhibitor, 5-aza-2′- deoxycytidine (5-Aza-CdR). Analysis of the promoter region of KPNA7 gene in CCL2 cells treated with 5-Aza-CdR showed a lighter methylation rate in all the CpG sites. Bioinformatic analysis predicted 4 miRNA-1296 binding sites in the coding region of KPNA7 mRNA. Ectopic co-expression of miRNA-1296 and KPNA7 in HEK293 cells led to reduced expression of KPNA7 protein. Quantitative real time PCR (RT-qPCR) analysis revealed that miRNA-1296 is expressed in oocytes and early stage embryos, and the expression reaches a peak level in 8-cell stage embryos, coincident with the time of embryonic genome activation and the start of declining of KPNA7 expression. Conclusions: These results suggest that DNA methylation may account for oocyte-specific expression of KPNA7, and miRNA-1296 targeting the coding region of KPNA7 is a potential mechanism for KPNA7 transcript degradation during the maternal-to-zygotic transition