Background
Emerging studies have shown that HOTAIR acts as an oncogene in gastric cancer (GC). However, its role in the extracellular matrix and in tumor immune infiltration remains unknown.
Methods
...HOTAIR and COL5A1 levels were analyzed by bioinformatics analysis and validated by qRT-PCR, western blotting and immunohistochemistry assays. The regulatory relationships between components of the HOTAIR/miR-1277-5p/COL5A1 axis and the role of this axis in GC were predicted by bioinformatics analysis, and validated by in vitro and in vivo experiments. The correlation between COL5A1 and GC immune infiltration was assessed by bioinformatics analysis and a COL5A1-based predictive nomogram was established using the Stomach Adenocarcinoma dataset from The Cancer Genome Atlas.
Results
We found that HOTAIR and COL5A1 were overexpressed in GC compared to normal controls, which predicted poor prognosis. The regulatory relationship of the HOTAIR/miR-1277-5p/COL5A1 axis in GC was demonstrated, and HOTAIR and COL5A1 were found to promote GC growth while miR-1277-5p exerted the reverse effects. In addition, COL5A1 was negatively associated with tumor purity but positively associated with immune infiltration, which suggested that COL5A1-mediated GC growth may be partially mediated by the regulation of immune infiltration. Additionally, the established COL5A1-based nomogram showed that COL5A1 can serve as a prognostic biomarker in GC.
Conclusions
HOTAIR regulates GC growth by sponging miR-1277-5p and upregulating COL5A1, and COL5A1-mediated GC cell proliferation may be mediated by effects on the tumor microenvironment, which provides novel targets for GC treatment.
To solve the problem in which the conventional ARMA modeling methods for gyro random noise require a large number of samples and converge slowly, an ARMA modeling method using a robust Kalman ...filtering is developed. The ARMA model parameters are employed as state arguments. Unknown time-varying estimators of observation noise are used to achieve the estimated mean and variance of the observation noise. Using the robust Kalman filtering, the ARMA model parameters are estimated accurately. The developed ARMA modeling method has the advantages of a rapid convergence and high accuracy. Thus, the required sample size is reduced. It can be applied to modeling applications for gyro random noise in which a fast and accurate ARMA modeling method is required.
Bayesian Networks in Fault Diagnosis Cai, Baoping; Huang, Lei; Xie, Min
IEEE transactions on industrial informatics,
10/2017, Letnik:
13, Številka:
5
Journal Article
Fault diagnosis is useful in helping technicians detect, isolate, and identify faults, and troubleshoot. Bayesian network (BN) is a probabilistic graphical model that effectively deals with various ...uncertainty problems. This model is increasingly utilized in fault diagnosis. This paper presents bibliographical review on use of BNs in fault diagnosis in the last decades with focus on engineering systems. This work also presents general procedure of fault diagnosis modeling with BNs; processes include BN structure modeling, BN parameter modeling, BN inference, fault identification, validation, and verification. The paper provides series of classification schemes for BNs for fault diagnosis, BNs combined with other techniques, and domain of fault diagnosis with BN. This study finally explores current gaps and challenges and several directions for future research.
Soil heavy metal pollution has been becoming serious and widespread in China. To date, there are few studies assessing the nationwide soil heavy metal pollution induced by industrial and agricultural ...activities in China. This review obtained heavy metal concentrations in soils of 402 industrial sites and 1041 agricultural sites in China throughout the document retrieval. Based on the database, this review assessed soil heavy metal concentration and estimated the ecological and health risks on a national scale. The results revealed that heavy metal pollution and associated risks posed by cadmium (Cd), lead (Pb) and arsenic (As) are more serious. Besides, heavy metal pollution and associated risks in industrial regions are severer than those in agricultural regions, meanwhile, those in southeast China are severer than those in northwest China. It is worth noting that children are more likely to be affected by heavy metal pollution than adults. Based on the assessment results, Cd, Pb and As are determined as the priority control heavy metals; mining areas are the priority control areas compared to other areas in industrial regions; food crop plantations are the priority control areas in agricultural regions; and children are determined as the priority protection population group. This paper provides a comprehensive ecological and health risk assessment on the heavy metals in soils in Chinese industrial and agricultural regions and thus provides insights for the policymakers regarding exposure reduction and management.
Display omitted
•402 industrial and 1041 agricultural sites are reviewed.•Pollution and risks in industrial regions were severer than agricultural regions.•30% of industrial sites pose potential non-carcinogenic risk.•The majority of As carcinogenic risks are at a relatively unacceptable range.•The priority control components were identified.
Fuel cells are an incredibly powerful renewable energy technology, but their broad applications remains lagging because of the high cost and poor reliability of cathodic electrocatalysts for the ...oxygen reduction reaction (ORR). This review focuses on the recent progress of ORR electrocatalysts in fuel cells. More importantly, it highlights the fundamental problems associated with the insufficient activity translation from rotating disk electrode to membrane electrode assembly in the fuel cells. Finally, for the atomic‐level in‐depth information on ORR catalysts in fuel cells, potential perspectives are suggested, including large‐scale preparation, unified assessment criteria, advanced interpretation techniques, advanced simulation and artificial intelligence. This review aims to provide valuable insights into the fundamental science and technical engineering for efficient ORR electrocatalysts in fuel cells.
Fuel cells are a powerful renewable energy technology. This review gives a comprehensive overview on oxygen reduction electrocatalysts towards practical fuel cells.
•This paper provides an exhaustive and comprehensive survey of phase shifting techniques used for fringe projection profilometry.•The basic principles of several state-of-the-art phase shifting ...profilometry algorithms are reviewed.•Typical error sources in phase measurement for a phase shifting profilometry system are reviewed and discussed.•The advantages and drawbacks of different algorithms are summarized to provide a useful guide to the selection of the most appropriate technique for a particular application.
The principle of structured light and triangulation is used in a wide range of 3D optical metrology applications, such as mechanical engineering, industrial monitoring, computer vision, and biomedicine. Among a multitude of techniques based on this principle, phase shifting profilometry (PSP) plays a dominant role due to its high attainable measurement accuracy, spatial resolution, and data density. Over the past few decades, many PSP algorithms have been proposed in the literature in order to achieve higher measurement accuracy, lower pattern count, and/or better robustness to different error sources. Besides, many unconventional PSP codification techniques address the problem of absolute phase recovery with few projected patterns, allowing for high-efficiency measurement of objects containing isolated regions or surface discontinuities. In this paper, we present an overview of these state-of-the-art phase shifting algorithms for implementing 3D surface profilometry. Typical error sources in phase measurement for a phase shifting system are discussed, and corresponding solutions are reviewed. The advantages and drawbacks of different PSP algorithms are also summarized to provide a useful guide to the selection of the most appropriate phase shifting technique for a particular application.
Departing from past research on managers' responses to employee voice, we propose and examine a nonlinear linkage between promotive/prohibitive voice and managers' evaluations of voicers (i.e., ...manager-rated voicers' promotability and overall performance). Drawing from social persuasion theory, we theorize that managers tend to give more positive evaluations to employees who engage in a moderate frequency of promotive/prohibitive voice than those who either rarely speak up or speak up very frequently. In Study 1, based on a sample from a Chinese bank, we found that leader-member exchange quality (LMX) moderated the inverted U-shaped linkage of prohibitive voice with manager-rated promotability of voicers, whereas the frequency of promotive voice was not related to promotability, irrespective of levels of LMX. In Study 2, using employee-reported voice frequency, rather than the manager-rated measures adopted in Study 1, we largely replicated the main findings of Study 1 based on a sample from an information technology firm in the United States. In Study 3, using another U.S. sample, from a financial services firm, we found that manager-perceived voice constructiveness mediated the curvilinear interactive effect of prohibitive voice (rather than promotive voice) and LMX on managers' evaluations of employees' overall performance.
•Four kinds of clinker with different alkali content were used to study the effect of alkali content on hydration.•A high alkali content accelerates hydration of cement at early ages and suppresses ...hydration at later ages.•Alkali addition promotes the dissolution of C3S and the formation of Ca(OH)2 but suppresses the formation of AFt.
The work aims to investigate the effect of alkali content in Portland cement on its hydration kinetics and mechanical properties. Four kinds of cement clinkers with different alkali content were chosen, and K2SO4 was added to adjust the alkali content of cement. The heat release of hydration, non–evaporable water content, electrical resistivity of the pastes and compressive strength of cements were tested. The hydration products, ion concentrations and pH value of the pore solution were analyzed. The results show that the alkali in cement accelerates the hydration at early ages but suppresses its hydration at later ages. Alkali addition increases the main heat evolution of cement with low alkali content and shortens the induction period of cement with high alkali content. The dissolution of C3S and the formation of Ca(OH)2 are promoted by alkali addition, but the formation of AFt is suppressed. Alkali addition is detrimental to the enhancement of the compressive strength of cement at later ages, the effect on the compressive strength at early ages is related to the total alkali content in cement. A positive effect is present in cement with low alkali content, the effect is negative in cement with high alkali content.
In recent years, intelligent driving technology based on vehicle–road cooperation has gradually become a research hotspot in the field of intelligent transportation. There are many studies regarding ...vehicle perception, but fewer studies regarding roadside perception. As sensors are installed at different heights, the roadside object scale varies violently, which burdens the optimization of networks. Moreover, there is a large amount of overlapping and occlusion in complex road environments, which leads to a great challenge of object distinction. To solve the two problems raised above, we propose RD-YOLO. Based on YOLOv5s, we reconstructed the feature fusion layer to increase effective feature extraction and improve the detection capability of small targets. Then, we replaced the original pyramid network with a generalized feature pyramid network (GFPN) to improve the adaptability of the network to different scale features. We also integrated a coordinate attention (CA) mechanism to find attention regions in scenarios with dense objects. Finally, we replaced the original Loss with Focal-EIOU Loss to improve the speed of the bounding box regression and the positioning accuracy of the anchor box. Compared to the YOLOv5s, the RD-YOLO improves the mean average precision (mAP) by 5.5% on the Rope3D dataset and 2.9% on the UA-DETRAC dataset. Meanwhile, by modifying the feature fusion layer, the weight of RD-YOLO is decreased by 55.9% while the detection speed is almost unchanged. Nevertheless, the proposed algorithm is capable of real-time detection at faster than 71.9 frames/s (FPS) and achieves higher accuracy than the previous approaches with a similar FPS.
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