Search

For a long time, the development of maritime communication has been restricted by the low data rate, high-latency and high cost of the current communication systems. The upgrade of new generation mobile communication technologies is attracting more and more attention to conduct a shore-based broadband mobile communication network with high-latency and high reliability to serve the maritime industries. This paper presents a solution by means of building a ship-to-infrastructure (S2I) and a ship-to-ship (S2S) wireless communication networks for an offshore region. We characterize the S2I and S2S channels at 5.9 GHz band based on the channel measurements in realistic environments. The channel characteristics, including power delay profile, delay spread, propagation path loss, are extracted and analyzed. In view of the difference between marine and terrestrial communications, we analyze the influencing factors of the offshore water, including effective reflection, divergence and shadowing from the water surface, and diffraction loss caused by the earth curvature. We also predict the power coverage range and the channel capacity for S2I and S2S wireless communications. Finally, the communication performance is evaluated according to the channel measurement and characterization analysis. The research results can be a reference for the construction of maritime communication networks., Safety and Security Science

This paper presents a bibliometric overview of the publications in the principal international journal Process Safety and Environmental Protection (PSEP) from 1990 to 2020 retrieved in the Web of Science (WoS) database to explore the evolution in safety and environmental engineering design and practice, as well as experimental or theoretical innovative research. Therefore, based on the WoS database and the visualization of similarities (VOS) viewer software, the bibliometric analysis and scientometric mapping of the literature have been performed from the perspectives of doc-ument types, publication and citation distribution over time, leading authors, countries (regions), institutions, the corresponding collaboration networks, most cited publications and references, fo-cused research fields and topics, research trend evolution over time, etc. The paper provides a comprehensive and quantitative overview and significant picture representation for the journal’s leading and evolutionary trends by employing specific aforementioned bibliometric analysis factors. In addition, by reviewing the evolutionary trends of the journal and the proposed investigated factors, such as the influential works, main research topics, and the research frontiers, this paper reveals the scientific literature production’s main research objectives and directions that could be addressed and explored in future studies., Safety and Security Science

Evidence of active tuberculosis (ATB) in patients with rheumatic diseases are research priorities but limited data from China have been reported. Research targeting patients not taking anti-TNF biologics are especially insufficient. We aimed to investigate the prevalence and risk factors of ATB in this at-risk population. We conducted a tertiary hospital-based, multi-center, cross-sectional study by using stratified multi-stage cluster sampling strategy to screen ATB in patients with rheumatic diseases. We estimated the prevalence of ATB in patients with rheumatic diseases and identified risk factors among those who were not taking anti-TNF biologic. A total of 13,550 eligible patients were enrolled, and the result showed the standardized prevalence of ATB according to the composition ratio of various types of rheumatic disease was 882/100000 (95% confidence interval (CI): 706-1057). Multivariable logistic regression analysis in patients not taking anti-TNF biologics showed that the independent risk factors of ATB were having systemic lupus erythematosus (SLE) (OR=2.722, 95% CI: 1.437-5.159, p=0.002), having Behcet's disease (BD) (OR= 5.261, 95% CI: 2.071-13.365, p<0.001), taking azathioprine(AZA) within the past two years (OR=2.095, 95% CI: 0.986-4.450, p=0.054), exposing to glucocorticoids ≥30mg/d for more than four weeks within the past two years (OR=2.031, 95% CI: 1.247-3.309, p=0.004) and having evidences of previous TB (OR= 6.185, 95% CI: 3.487-10.969, p<0.001). The prevalence of ATB was higher in patients with rheumatic diseases compared to the general population. Patients with SLE or BD, prolonged exposure to moderate to high dose of glucocorticoids and previous TB were independent risk factors for ATB.

This paper proposes a dual-supervised uncertainty inference (DS-UI) framework for improving Bayesian estimation-based UI in DNN-based image recognition. In the DS-UI, we combine the classifier of a DNN, i.e., the last fully-connected (FC) layer, with a mixture of Gaussian mixture models (MoGMM) to obtain an MoGMM-FC layer. Unlike existing UI methods for DNNs, which only calculate the means or modes of the DNN outputs' distributions, the proposed MoGMM-FC layer acts as a probabilistic interpreter for the features that are inputs of the classifier to directly calculate the probabilities of them for the DS-UI. In addition, we propose a dual-supervised stochastic gradient-based variational Bayes (DS-SGVB) algorithm for the MoGMM-FC layer optimization. Unlike conventional SGVB and optimization algorithms in other UI methods, the DS-SGVB not only models the samples in the specific class for each Gaussian mixture model (GMM) in the MoGMM, but also considers the negative samples from other classes for the GMM to reduce the intra-class distances and enlarge the inter-class margins simultaneously for enhancing the learning ability of the MoGMM-FC layer in the DS-UI. Experimental results show the DS-UI outperforms the state-of-the-art UI methods in misclassification detection. We further evaluate the DS-UI in open-set out-of-domain/-distribution detection and find statistically significant improvements. Visualizations of the feature spaces demonstrate the superiority of the DS-UI. Codes are available at https://github.com/PRIS-CV/DS-UI.

Recently, the extensive discharge of oily sludge, due to excessive use of fossil oil, has become a serious worldwide concern, as it leads to serious environmental pollution and even threat human health. However, the complex properties and compositions of oily sludge make it difficult for the treatment of oily sludge. This study proposed a novel method of combined degradation of oily sludge by surfactants with activated-persulfate, and analyzed the degradation efficiency and degradation pathway. The organics in oil sludge were eluted by surfactant, and the residual oil difficult to be eluted was further oxidized by activated persulfate. The combined method significantly improved the degradation efficiency of oily sludge, and the removal rate reached 94.6 ± 2.8%, and the oil content of the residual oily sludge was 0.57%, which had reached the discharge standard. The mechanism analysis indicated that surfactant could increase the solubility of oil by reducing the surface tension, and the hydroxyl radical and sulfate radical generated by activated persulfate could degrade the complex organic matters into small molecule matters, achieving efficient degradation of oil sludge. This work demonstrated a new avenue for the efficient and cost-effective treatment of oily sludge, opening an environmentally friendly treatment concept.