Research and Implement of an Algorithm for Physical Topology Automatic Discovery in Switched Ethernet

AbstractIn this paper, a novel practical algorithmic solution for automatic discovering the physical topology of switched Ethernet was proposed. Our algorithm collects standard SNMP MIB information that is widely supported in modern IP networks and then builds the physical topology of the active network. We described the relative definitions, system model and proved the correctness of the algorithm. Practically, the algorithm was implemented in our visualization network monitoring system. We also presented the main steps of the algorithm, core codes and running results on the lab network. The experimental results clearly validate our approach, demonstrating that our algorithm is simple and effective which can discover the accurate up-to-date physical network topology

Characteristics of buried paleo-channels in the Western South Yellow Sea during the Late Last Glaciation

Istraživanja o evoluciji paleolitskih korita u obalnim područjima važna su za konstrukcije podmorskog inženjerstva i za otkrivanje promjena u globalnom paleolitskom okruženju. Stoga je za istraživanje značajki paleo-korita tijekom kasnog posljednjeg ledenog doba u zapadnom Južnom Žutom moru primijenjena digitalna metoda analize terena i ArcGis funkcija porijekla rijeke, analizirani su plitki stratigrafski seizmički profili visoke rezolucije i osnovni podaci, a rabljene su empirijske formule rijeke za određivanje riječnih svojstava i struktura. Rezultati pokazuju da je drevni riječni sustav tijekom kasnog posljednjeg ledenog doba grebena Južnog Žutog mora podijeljen na paleo-Žutu (Huanghe) i paleo-Yangtze (Changjiang) rijeku. Paleo-korita blizu 33°N pripadaju paleo-Yangtze rijeci i uglavnom teku od istoka do sjeveroistoka. Paleo-korita oko 35°N i 123,5°E dio su paleo-Žute rijeke. U usporedbi s paleo-Žutom rijekom, paleo-Yangtze rijeka inklinira horizontalnom premiještanju, ima veću prodornu moć i veću količinu vode. Na temelju metode širine nagiba sustav paleo-Žute rijeke može se smatrati uglavnom krivudavim dok je sustav paleo-Yangtze rijeke uglavnom sustav račvaste (braided) rijeke. Pronađene su značajne razlike između paleo-Yangtze rijeke i paleo-Žute rijeke. Značajke podzemnih paleo-korita tijekom kasnog posljednjeg ledenog doba mogu biti korisne u predviđanju popratne moguće opasnosti kod podvodnih konstrukcija i otkrivanju promjena paleookruženja u grebenu Južnog Žutog mora.Studies on the evolution of paleo-channels in coastal areas are important for submarine engineering construction and to reveal changes in the global paleoenvironment. Thus, to explore the characteristics of paleo-channels during the late Last Glaciation in the western South Yellow Sea, digital terrain analysis method and ArcGis river extraction function were employed, high-resolution shallow stratigraphic seismic profiles and core data were analysed, and river empirical formulas were used to determine river properties and river patterns. Results indicate that the ancient river system during the late Last Glaciation of the South Yellow Sea shelf is divided into paleo-Yellow (Huanghe) and paleo-Yangtze (Changjiang) Rivers. The paleo-channels near 33°N belong to the paleo-Yangtze River, and generally flow from east to northeast. The paleo-channels around 35°N and 123,5°E are part of the paleo-Yellow River. Compared with the paleo-Yellow River, the paleo-Yangtze River is prone to horizontal migration and has higher penetration depths and discharge. Based on the slope-width method, the paleo-Yellow River system can be considered mainly as a meandering river, whereas the paleo-Yangtze River system is largely a braided river. Remarkable differences are found between the paleo-Yangtze River and the paleo-Yellow River. The characteristics of buried paleo-channels during the late Last Glaciation can be useful in predicting the incident potential hazard of submarine engineering and in revealing the paleoenvironment changes in the South Yellow Sea shelf

Exogenous Melatonin Improves Cold Tolerance of Strawberry (Fragaria × ananassa Duch.) through Modulation of DREB/CBF-COR Pathway and Antioxidant Defense System

The strawberry (Fragaria × ananassa Duch.) is an important fruit crop cultivated worldwide for its unique taste and nutritional properties. One of the major risks associated with strawberry production is cold damage. Recently, melatonin has emerged as a multifunctional signaling molecule that influences plant growth and development and reduces adverse consequences of cold stress. The present study was conducted to investigate the defensive role of melatonin and its potential interrelation with abscisic acid (ABA) in strawberry plants under cold stress. The results demonstrate that melatonin application conferred improved cold tolerance on strawberry seedlings by reducing malondialdehyde and hydrogen peroxide contents under cold stress. Conversely, pretreatment of strawberry plants with 100 μM melatonin increased soluble sugar contents and different antioxidant enzyme activities (ascorbate peroxidase, catalase, and peroxidase) and non-enzymatic antioxidant (ascorbate and glutathione) activities under cold stress. Furthermore, exogenous melatonin treatment stimulated the expression of the DREB/CBF—COR pathways’ downstream genes. Interestingly, ABA treatment did not change the expression of the DREB/CBF—COR pathway. These findings imply that the DREB/CBF-COR pathway confers cold tolerance on strawberry seedlings through exogenous melatonin application. Taken together, our results reveal that melatonin (100 μM) pretreatment protects strawberry plants from the damages induced by cold stress through enhanced antioxidant defense potential and modulating the DREB/CBF—COR pathway. View Full-Tex

System log detection model based on conformal prediction

With the rapid development of the Internet of Things, the combination of the Internet of Things with machine learning, Hadoop and other fields are current development trends. Hadoop Distributed File System (HDFS) is one of the core components of Hadoop, which is used to process files that are divided into data blocks distributed in the cluster. Once the distributed log data are abnormal, it will cause serious losses. When using machine learning algorithms for system log anomaly detection, the output of threshold‐based classification models are only normal or abnormal simple predictions. This paper used the statistical learning method of conformity measure to calculate the similarity between test data and past experience. Compared with detection methods based on static threshold, the statistical learning method of the conformity measure can dynamically adapt to the changing log data. By adjusting the maximum fault tolerance, a system administrator can better manage and monitor the system logs. In addition, the computational efficiency of the statistical learning method for conformity measurement was improved. This paper implemented an intranet anomaly detection model based on log analysis, and conducted trial detection on HDFS data sets quickly and efficiently.This research was funded by the Guangdong Province Key Area R&D Program of China under Grant No. 2019B010137004; the National Natural Science Foundation of China under Grant No.61871140, No. U1636215, and No. 61972108; the National Key Research and Development Plan under Grant No. 2018YFB0803504; Civil Aviation Safety Capacity Building Project; and Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme (2019)

Polycomb CBX7 Directly Controls Trimethylation of Histone H3 at Lysine 9 at the p16 Locus

BACKGROUND: H3K9 trimethylation (H3K9me3) and binding of PcG repressor complex-1 (PRC1) may play crucial roles in the epigenetic silencing of the p16 gene. However, the mechanism of the initiation of this trimethylation is unknown. METHODOLOGY/PRINCIPAL FINDINGS: In the present study, we found that upregulating the expression of PRC1 component Cbx7 in gastric cancer cell lines MGC803 and BGC823 led to significantly suppress the expression of genes within the p16-Arf-p15 locus. H3K9me3 formation was observed at the p16 promoter and Regulatory Domain (RD). CBX7 and SUV39H2 binding to these regions were also detectable in the CBX7-stably upregulated cells. CBX7-SUV39H2 complexes were observed within nucleus in bimolecular fluorescence complementation assay (BiFC). Mutations of the chromodomain or deletion of Pc-box abolished the CBX7-binding and H3K9me3 formation, and thus partially repressed the function of CBX7. SiRNA-knockdown of Suv39h2 blocked the repressive effect of CBX7 on p16 transcription. Moreover, we found that expression of CBX7 in gastric carcinoma tissues with p16 methylation was significantly lower than that in their corresponding normal tissues, which showed a negative correlation with transcription of p16 in gastric mucosa. CONCLUSION/SIGNIFICANCE: These results demonstrated for the first time, to our knowledge, that CBX7 could initiate H3K9me3 formation at the p16 promoter

A Systematic Molecular Pathology Study of a Laboratory Confirmed H5N1 Human Case

Autopsy studies have shown that human highly pathogenic avian influenza virus (H5N1) can infect multiple human organs other than just the lungs, and that possible causes of organ damage are either viral replication and/or dysregulation of cytokines and chemokines. Uncertainty still exists, partly because of the limited number of cases analysed. In this study, a full autopsy including 5 organ systems was conducted on a confirmed H5N1 human fatal case (male, 42 years old) within 18 hours of death. In addition to the respiratory system (lungs, bronchus and trachea), virus was isolated from cerebral cortex, cerebral medullary substance, cerebellum, brain stem, hippocampus ileum, colon, rectum, ureter, aortopulmonary vessel and lymph-node. Real time RT-PCR evidence showed that matrix and hemagglutinin genes were positive in liver and spleen in addition to positive tissues with virus isolation. Immunohistochemistry and in-situ hybridization stains showed accordant evidence of viral infection with real time RT-PCR except bronchus. Quantitative RT-PCR suggested that a high viral load was associated with increased host responses, though the viral load was significantly different in various organs. Cells of the immunologic system could also be a target for virus infection. Overall, the pathogenesis of HPAI H5N1 virus was associated both with virus replication and with immunopathologic lesions. In addition, immune cells cannot be excluded from playing a role in dissemination of the virus in vivo

Inverse Free Parallel Spectral Divide and Conquer Algorithms for Nonsymmetric Eigenproblems

We discuss two inverse free, highly parallel, spectral divide and conquer algorithms: one for computing an invariant subspace of a nonsymmetric matrix and another one for computing left and right deflating subspaces of a regular matrix pencil A 0 B. These two closely related algorithms are based on earlier ones of Bulgakov, Godunov and Malyshev, but improve on them in several ways. These algorithms only use easily parallelizable linear algebra building blocks: matrix multiplication and QR decomposition. The existing parallel algorithms for the nonsymmetric eigenproblem use the matrix sign function, which is faster but can be less stable than the new algorithm. Appears also as ffl Research Report 94-01, Department of Mathematics, University of Kentucky. ffl University of California at Berkeley, Computer Science Division Report UCB//CSD-94-793. It is also available by anonymous ftp on tr-ftp.cs.berkeley.edu, in directory pub/tech-reports/cs/csd94 -793. ffl Lawrence Berkeley Laboratory..

Valid Probabilistic Anomaly Detection Models for System Logs

System logs can record the system status and important events during system operation in detail. Detecting anomalies in the system logs is a common method for modern large-scale distributed systems. Yet threshold-based classification models used for anomaly detection output only two values: normal or abnormal, which lacks probability of estimating whether the prediction results are correct. In this paper, a statistical learning algorithm Venn-Abers predictor is adopted to evaluate the confidence of prediction results in the field of system log anomaly detection. It is able to calculate the probability distribution of labels for a set of samples and provide a quality assessment of predictive labels to some extent. Two Venn-Abers predictors LR-VA and SVM-VA have been implemented based on Logistic Regression and Support Vector Machine, respectively. Then, the differences among different algorithms are considered so as to build a multimodel fusion algorithm by Stacking. And then a Venn-Abers predictor based on the Stacking algorithm called Stacking-VA is implemented. The performances of four types of algorithms (unimodel, Venn-Abers predictor based on unimodel, multimodel, and Venn-Abers predictor based on multimodel) are compared in terms of validity and accuracy. Experiments are carried out on a log dataset of the Hadoop Distributed File System (HDFS). For the comparative experiments on unimodels, the results show that the validities of LR-VA and SVM-VA are better than those of the two corresponding underlying models. Compared with the underlying model, the accuracy of the SVM-VA predictor is better than that of LR-VA predictor, and more significantly, the recall rate increases from 81% to 94%. In the case of experiments on multiple models, the algorithm based on Stacking multimodel fusion is significantly superior to the underlying classifier. The average accuracy of Stacking-VA is larger than 0.95, which is more stable than the prediction results of LR-VA and SVM-VA. Experimental results show that the Venn-Abers predictor is a flexible tool that can make accurate and valid probability predictions in the field of system log anomaly detection