Multi-classifier information fusion in risk analysis

This paper develops a novel multi-classifier information fusion approach that integrates the probabilistic support vector machine (SVM) and the improved Dempster-Shafer (D-S) evidence theory to support risk analysis under uncertainty. Safety levels for various risk factors can be classified separately using the probabilistic SVM. Then, these multiple classification results will be fused at the decision level to achieve an overall risk evaluation by an improved D-S evidence theory with the integration of the Dempster’ rule and the weighted average rule. The Monte Carlo simulation approach is employed to model the randomness and uncertainty underlying limited observations. A global sensitivity analysis is performed to identify the most significant factors contributing to the risk event. A realistic operational tunnel case in China is used to demonstrate the feasibility and effectiveness of the developed approach, aiming to assess the magnitude of the structural health risk. Results indicate the developed SVM-DS approach is capable of (1) Fusing multi-classifier information effectively from different SVM models with a high classification accuracy of 97.14%; (2) Performing a strong robustness to bias, which can achieve acceptable classification accuracy even under a 20% bias; and (3) Exhibiting a more outstanding classification performance (87.99% accuracy) than the single SVM model (63.84% accuracy) under a high bias (20%). Since the proposed reliable risk analysis method can efficiently fuse multi-sensory information with ubiquitous uncertainties, conflicts, and bias, it provides in-depth analysis for structural health status together with the most critical risk factors, and then proper remedial actions can be taken at an early stage.Ministry of Education (MOE)Nanyang Technological UniversitySubmitted/Accepted versionThe National Key Research Projects of China (Grant No. 2016YFC0800208), the Start-Up Grant at Nanyang Technological University, Singapore (No. M4082160.030), the Ministry of Education Tier 1 Grant, Singapore (No. M4011971.030), and the National Natural Science Foundation of China (Grant Nos. 51578260 and 71571078) are acknowledged for their financial support of this research

Vegetation classification of Stipa steppes in China, with reference to the International Vegetation Classification

Aims: The vegetation classification system of China (China-VCS) is not completed. Stipa steppes are the most important steppes in China. Here we made optimal use of available plot data to classify Stipa steppes into associations in a way that is consistent with International Vegetation Classification. Study Area: the Songnen Plain, Inner Mongolian Plateau, Loess Plateau, Tibetan Plateau, and the northwest mountain areas of China. Methods: We used 1337 plots to partition the Stipa steppes of China into clusters using hierarchical clustering. Supervised noise clustering was used to improve the classifications at the group, alliance, and association levels. Non-metric multidimensional scaling ordination was used to visualize the homogeneity of plots within each cluster, and we overlaid site and climatic vectors. Diagnostic species were identified for each cluster using Indicator Species Analysis. Results: We defined five biogeographic groups, 26 alliances, 91 associations, and 12 communities of Stipa steppes of China. The Stipa-dominated alliances in the framework of the current China-VCS were verified, but the four vegetation subformations of Tussock Steppe were not completely supported by this study. Conclusions: This is the first systematical and comprehensive classification for Stipa steppes in China based on plot data. Our classification used a set of dominant species and diagnostic species to define biogeogrpahic groups, alliances and associations, ensuring compatibility with the International Vegetation Classification. Taxonomic reference: Flora Reipublicae Popularis Sinicae, Flora of China Abbreviations: AMT = Annual Mean Temperature; AP = Annual Precipitation; China-VCS = vegetation classification system of China; IVC = international vegetation classification; MTCQ = Mean Temperature of Coldest Quarter; MTWQ = Mean Temperature of Warmest Quarter; NC = noise clustering; NMDS = non-metric multidimensional scaling; PDQ = Precipitation of Driest Quarter; PS = Precipitation Seasonality; PWQ = Precipitation of Wettest Quarter; TS = Temperature Seasonalit

Modeling face reliability in tunneling : a copula approach

This research develops a copula-enabled approach for modeling and assessing the reliability of the dependent system with incomplete probability information. A bivariate framework consisting of the supporting pressure and the ground settlement is proposed to estimate the excavation face reliability in tunneling under limited observations. The impacts of the selection of copula functions, the variation of the failure criteria, and the size of the measured data and Monte Carlo simulation sampling on the reliability estimation result are explored. A realistic tunnel case in the Wuhan metro system, China, is used to demonstrate the applicability and effectiveness of the developed approach. Results indicate that: (1) the failure probability will lead to an overestimated result, which is more than twice of the reference value (that is without considering the negative dependence); (2) the commonly used Gaussian copula function is likely to underestimate the failure probability and lead to less conservative designs; (3) a setting size of 10 5 samples is reasonable in the case to achieve the required quality in estimation; and (4) the failure probability gradually rises along with an increase of the limit value of the supporting pressure and decreases along with an increase of the limit value of the ground settlement.Nanyang Technological UniversityThe National Key Research Projects of China (Grant No. 2016YFC0800208), the Start-Up Grant at Nanyang Technological University, Singapore (No. M4082160.030), and the National Natural Science Foundation of China (Grant Nos. 51778262 and 71571078) are acknowledged for their financial support of this research

Response of Plant Height, Species Richness and Aboveground Biomass to Flooding Gradient along Vegetation Zones in Floodplain Wetlands, Northeast China.

Flooding regime changes resulting from natural and human activity have been projected to affect wetland plant community structures and functions. It is therefore important to conduct investigations across a range of flooding gradients to assess the impact of flooding depth on wetland vegetation. We conducted this study to identify the pattern of plant height, species richness and aboveground biomass variation along the flooding gradient in floodplain wetlands located in Northeast China. We found that the response of dominant species height to the flooding gradient depends on specific species, i.e., a quadratic response for Carex lasiocarpa, a negative correlation for Calamagrostis angustifolia, and no response for Carex appendiculata. Species richness showed an intermediate effect along the vegetation zone from marsh to wet meadow while aboveground biomass increased. When the communities were analysed separately, only the water table depth had significant impact on species richness for two Carex communities and no variable for C. angustifolia community, while height of dominant species influenced aboveground biomass. When the three above-mentioned communities were grouped together, variations in species richness were mainly determined by community type, water table depth and community mean height, while variations in aboveground biomass were driven by community type and the height of dominant species. These findings indicate that if habitat drying of these herbaceous wetlands in this region continues, then two Carex marshes would be replaced gradually by C. angustifolia wet meadow in the near future. This will lead to a reduction in biodiversity and an increase in productivity and carbon budget. Meanwhile, functional traits must be considered, and should be a focus of attention in future studies on the species diversity and ecosystem function in this region

Interleukin-6 and insulin-like growth factor-1 synergistically promote the progression of NSCLC

The signaling pathways of interleukin-6 (IL-6) and insulin-like growth factor 1 (IGF-1) play an important role in the progression of lung cancer, and this study aimed to explore whether they can synergistically promote the progression of non-small cell lung cancer (NSCLC). We found that IL-6, glycoprotein 130 (GP130), IGF-1 and IGF-1R were highly expressed in NSCLC (p = .000), and there was the correlation between GP130, IGF-1, and IGF-1R (p < .01). The overall survival of patients with the co-expression of GP130 and IGF-1R was significantly shorter (p = .0360). Co-stimulation of IL-6 and IGF-1 resulted in significantly enhanced in cell proliferation, (p < .05), invasion (p < .05), cycle (p < .05), apoptosis (p < .05), and the expression of signal molecules (GP130, IGF-1R, p-AKT, and p-ERK1/2) (all p < .05) in NSCLC cells. This experiment revealed that IL-6 and IGF-1 can synergistically promote the progression of NSCLC. The high expression of GP130 and IGF-1R is an independent risk factor for poor prognosis patients, and it is helpful to find a more accurate target for targeted therapy in NSCLC

Evolution of polycyclic aromatic hydrocarbons in the surface sediment of southern Jiaozhou Bay in northern China after an accident of oil pipeline explosion.

The 2013 "Qingdao oil pipeline explosion" contaminated about 2.5 km of shoreline in the Jiaozhou Bay area and aroused widespread concern because of the serious casualties even though it was not the most severe oil-spill contamination in China. To evaluate the long-term impact, we collected thirty-three surface sediment samples after 3 years of the accident, with sixteen polycyclic aromatic hydrocarbons (PAHs) detected. Spatial-temporal variation in PAHs revealed that a minimal impact might still be present after 3 years. Source analysis combined with a one-way ANOVA showed that pyrolytic sources were consistently predominant. The environmental impact was already minimal 3 years later and negligible thereafter. Although the cancer risk has decreased over the years, there has always been a potential hazard to human for specific occupation, with all of the risk values exceeded 10 . This study offers a reference for assessing the long-term impact of oil spills in similar bay areas. [Abstract copyright: Copyright © 2022 Elsevier Ltd. All rights reserved.

Smooth bromegrass seed yield and yield component responses to seeding rates and row spacings in two climates

Successful grass seed production depends on identifying a suitable environment for the species and proper agronomic practices. Previous research on many species has addressed identifying appropriate agronomic practices for grass seed production, but these studies have not evaluated the effects of environment. By conducting the same experiments in Jiuquan, China (a desert climate) and Tongliao, China (a semiarid continental monsoon climate), the effects of environment, seeding rate, row spacing and their interactions were determined for smooth bromegrass (Bromus inermis Leyss) seed production. Three seeding rates (.3, .5, and .7 g m−1 pure live seed) and four row spacings (30, 50, 70, and 90 cm) were evaluated over three years. Jiuquan had comparable seed yield (SY) and greater thousand-seed weight (TSW) than Tongliao. Three-year average SY decreased with increased row spacings at both sites. Results suggest that in both climates, successful smooth bromegrass seed production was possible, but greater TSW is predicted for desert climates with good irrigation conditions than in semiarid continental monsoon climates due to greater sunshine duration (574 h compared with 527 h) and low relative humidity during seed development (48% vs. 66%). A seeding rate of .3 g m−1 and a row spacing of no wider than 30 cm appears to be adequate for smooth bromegrass seed production in these research locations and in similar ecological regions around the world

Clinical characteristics from co-infection with avian influenza A H7N9 and Mycoplasma pneumoniae: a case report

Abstract Background More and more cases of human infections with avian influenza A H7N9 have been reported since it was first mentioned in 2013 in China, but concurrence of influenza A H7N9 with Mycoplasma pneumoniae, however, has never been described. Here, we reported the case of a woman co-infected by influenza A H7N9 and Mycoplasma pneumoniae, whose treatment process was a little bit longer and a little bit complicated as well. Case presentation Our patient was an 80-year-old Chinese woman who presented with fever, cough, chest tightness, and shortness of breath. A computed tomography scan showed obvious infiltrations at lower parts of both lungs. Arterial blood gas analysis confirmed a severe respiratory failure (type I). Her sputum and throat swabs were checked for nucleic acid of influenza A and the result was positive for influenza A H7N9. She was diagnosed as having severe influenza A H7N9 and acute respiratory distress syndrome, and was admitted to an intensive care unit. She was given comprehensive treatment, including oseltamivir, methylprednisolone, immunoglobulin, gastric protection, and noninvasive mechanical ventilation. Her condition improved 4 days later. However, some symptoms exacerbated again 2 days later with ground-glass changes appearing in upper area of right lung and the titer of antibody to Mycoplasma pneumoniae rising from 1:80 to 1:640. She was reasonably considered to be infected with Mycoplasma pneumoniae as well, and azithromycin and moxifloxacin were added to her treatment. Oseltamivir was discontinued because of three consecutive negative results of nucleic acid for influenza A H7N9, but anti-Mycoplasma treatment was continued. Although her symptoms and abnormal changes on computed tomography scan slowly went away, she finally recovered from the mixed infection after a total of 33 days of management. Conclusion In patients with confirmed influenza A H7N9 infection whose condition worsens again, especially with new infiltration or lung ground-glass infiltration, one should suspect infection by other pathogens such as Mycoplasma pneumoniae