The Path and Enlightenment of Data-Driven Digital Transformation of Organizational Learning ——A Case Study of the Practice of China Telecom

This paper took China Telecom as a case. It has analyzed data-driven digital transformation in organizational learning, and summarized the methods and enlightenments of digital transformation

Container Terminal Berth-Quay Crane Capacity Planning Based on Markov Chain

This paper constructs a berth-quay crane capacity planning model with the lowest average daily cost in the container terminal, and analyzes the influence of the number of berths and quay cranes on the terminal operation. The object of berth-quay crane capacity planning is to optimize the number of berths and quay cranes to maximize the benefits of the container terminal. A steady state probability transfer model based on Markov chain for container terminal is constructed by the historical time series of the queuing process. The current minimum time operation principle (MTOP) strategy is proposed to correct the state transition probability of the Markov chain due to the characteristics of the quay crane movement to change the service capacity of a single berth. The solution error is reduced from 7.03% to 0.65% compared to the queuing theory without considering the quay crane movement, which provides a basis for the accurate solution of the berth-quay crane capacity planning model. The proposed berth-quay crane capacity planning model is validated by two container terminal examples, and the results show that the model can greatly guide the container terminal berth-quay crane planning

The Recovery of Weak Impulsive Signals Based on Stochastic Resonance and Moving Least Squares Fitting

In this paper a stochastic resonance (SR)-based method for recovering weak impulsive signals is developed for quantitative diagnosis of faults in rotating machinery. It was shown in theory that weak impulsive signals follow the mechanism of SR, but the SR produces a nonlinear distortion of the shape of the impulsive signal. To eliminate the distortion a moving least squares fitting method is introduced to reconstruct the signal from the output of the SR process. This proposed method is verified by comparing its detection results with that of a morphological filter based on both simulated and experimental signals. The experimental results show that the background noise is suppressed effectively and the key features of impulsive signals are reconstructed with a good degree of accuracy, which leads to an accurate diagnosis of faults in roller bearings in a run-to failure test

A quantitative diagnosis method for rolling element bearing using signal complexity and morphology filtering

This paper considers a quantitative method for assessment of fault severity of rolling element bearing by means of signal complexity and morphology filtering. The relationship between the complexity and bearing fault severity is explained. The improved morphology filtering is adopted to avoid the ambiguity between severity fault and the pure random noise since both of them will acquire higher complexity value. According to the attenuation signal characteristics of a faulty bearing the artificial immune optimization algorithm with the target of pulse index is used to obtain optimal filtering signal. Furthermore, complexity algorithm is revised to avoid the loss of weak impact signal. After largely removing noise and other unrelated signal components, the complexity value will be mostly affected by the bearing system and therefore may be adopted as a reliable quantitative bearing fault diagnosis method. Application of the proposed approach to the bearing fault signals has demonstrated that the improved morphology filtering and the complexity of signal can be used to adequately evaluate bearing fault severity

Expression and localization of apolipoprotein M in human colorectal tissues

<p>Abstract</p> <p>Background</p> <p>It has been well documented that apolipoprotein M (apoM) is principally expressed in the liver and kidney. However we found that there was weak apoM expression in other tissues or organs too, which could not be ignored. In the present study, we therefore examined apoM expression in human colorectal tissues including cancer tissues, cancer adjacent normal tissues, polyp tissues and normal mucosa as well as inflammatory mucosa.</p> <p>Methods</p> <p>Tissue samples were collected from patients who underwent surgical resection or endoscopic examination. ApoM mRNA levels were determined by the real-time RT-PCR and apoM protein mass were examined by the immunohistochemistry.</p> <p>Results</p> <p>ApoM protein can be detected in all colorectal tissues. However, apoM protein mass were significantly lower in the cancer tissues than its matched adjacent normal tissues, polyp tissues, normal mucosa and inflammatory mucosa. In parallel, apoM mRNA levels in the colorectal cancer tissues (0.0536 ± 0.0131) were also significantly lower than those in their adjacent normal tissues (0.1907 ± 0.0563) (<it>P </it>= 0.033). Interestingly, apoM mRNA levels in colorectal cancer tissues were statistic significant higher in the patients with lymph node metastasis than the patients without lymph node metastasis (<it>P </it>= 0.008). Patients under Dukes' C and D stages had much higher apoM mRNA levels than patients under Dukes' A and B stages (<it>P </it>= 0.034).</p> <p>Conclusion</p> <p>It is concluded that apoM could also be expressed in human colorectal tissues besides liver and kidney. ApoM mRNA levels in the colorectal cancer tissues were significantly increased in the patients with lymph node metastasis. Whether increased apoM expression in the patients with lymph node metastasis being related to patients' prognosis and the physiopathological importance of apoM expression in colorectal tissues need further investigation.</p

Privacy-Preserving Individual-Level COVID-19 Infection Prediction via Federated Graph Learning

Accurately predicting individual-level infection state is of great value since its essential role in reducing the damage of the epidemic. However, there exists an inescapable risk of privacy leakage in the fine-grained user mobility trajectories required by individual-level infection prediction. In this paper, we focus on developing a framework of privacy-preserving individual-level infection prediction based on federated learning (FL) and graph neural networks (GNN). We propose Falcon, a Federated grAph Learning method for privacy-preserving individual-level infeCtion predictiON. It utilizes a novel hypergraph structure with spatio-temporal hyperedges to describe the complex interactions between individuals and locations in the contagion process. By organically combining the FL framework with hypergraph neural networks, the information propagation process of the graph machine learning is able to be divided into two stages distributed on the server and the clients, respectively, so as to effectively protect user privacy while transmitting high-level information. Furthermore, it elaborately designs a differential privacy perturbation mechanism as well as a plausible pseudo location generation approach to preserve user privacy in the graph structure. Besides, it introduces a cooperative coupling mechanism between the individual-level prediction model and an additional region-level model to mitigate the detrimental impacts caused by the injected obfuscation mechanisms. Extensive experimental results show that our methodology outperforms state-of-the-art algorithms and is able to protect user privacy against actual privacy attacks. Our code and datasets are available at the link: https://github.com/wjfu99/FL-epidemic.Comment: accepted by TOI

Expression of apolipoprotein M in human hepatocellular carcinoma tissues

The present study examined mRNA levels and protein mass of apolipoprotein M (apoM) in human hepatocellular carcinoma (HCC) tissues and in the adjacent tissues. Plasma apoM levels in these HCC patients were also determined and compared to the normal subjects. The mean level of plasma apoM in the HCC patients was 0.61 +/- 0.30 OD mm(-2), which was significantly higher than that in the normal subjects 0.37 +/- 0.07 OD mm(-2) (P < 0.01). However, both apoM mRNA levels and apoM protein mass in the HCC tissues were significantly lower than in the adjacent tissues (P < 0.05). It is concluded that human hepatocellular carcinoma tissues had a reduced capacity to produce apoM than the adjacent non-tumor tissues. However, the plasma apoM levels were higher in the HCC patients than in normal subjects, which suggested that tissues adjacent to the tumors or extra-hepatic apoM production in the HCC patients may contribute to the higher plasma apoM levels in these patients. The clinical significance of apoM in relation to HCC still needs further investigation. (C) 2009 Published by Elsevier GmbH

In silico screening of potentially bioactive-anti-functional dyspepsia constituents of Magnoliae officinalis Cortex based on molecular docking and network pharmacology

Purpose: To screen for bioactive anti-functional dyspepsia compounds from Magnoliae officinalis Cortex (Hou Po) and to identify the mechanism(s) of action involved.Methods: The compounds of Hou Po were collected from the literature. The related target proteins were identified from DrugBank. Through&nbsp; “Libdock” module of Discovery Studio 3.5, the compounds were matched with related target proteins. Taking the Libdock score of the original ligand with target protein as standard, components with higher scores than this standard were considered as potential bioactive compounds. Based on Cytoscape software, the interaction networks of the bioactive compound-target protein complexes were mapped. On the other hand, the online DAVID database was used to analyze the GO enrichment and KEGG pathway of each target.Results: A total of 199 chemical constituents and 13 correlated target proteins were obtained. One hundred and thirty-nine (139) potential bioactive constituents were acquired based on molecular docking. Thirty-one (31) bioactive compounds were selected based on degree values in networkanalysis. “Palmitone” and “magnolignan G” which had the highest degree values were considered promising and leading compounds. The result of gene enrichment analysis showed that the bioactive compounds exerted their effects mainly via “neuroactive ligand-receptor interaction” pathway and “Cholinergic synapse” pathways.Conclusion: Based on molecular docking and network pharmacology technique, the material basis for the use of Hou Po in the treatment of FD has been revealed. This finding provides a useful guide in the development of Hou Po-based anti-FD drugs. Keywords: Magnolia officinalis, Hou Po, Molecular docking, Functional dyspepsia, Network pharmacolog