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As CO2 emissions continue to rise, the problem of global warming is becoming increasingly serious. It is important to provide a robust management decision-making basis for the reductions of carbon emissions worldwide by predicting carbon emissions accurately. However, affected by various factors, the prediction of carbon emissions is challenging due to its nonlinear and nonstationary characteristics. Thus, we propose a combination forecast model, named CEEMDAN-GWO-SVR, which incorporates multiple features to predict trends in China's carbon emissions. First, the impact of online search attention and public health emergencies are considered in carbon emissions prediction. Since the impact of different variables on carbon emissions is lagged, the grey relational degree is used to identify the appropriate lag series. Second, irrelevant features are eliminated through RFECV. To address the issue of feature redundancy of online search attention, we propose a dimensionality reduction method based on keyword classification. Finally, to evaluate the features of the proposed framework, four evaluation indicators are tested in multiple machine learning models. The best-performed model (SVR) is optimized by CEEMDAN and GWO to enhance prediction accuracy. The empirical results indicate that the proposed framework maintains good performance in both multi-scenario and multi-step prediction. [ABSTRACT FROM AUTHOR]

Ranaviruses are globally emerging pathogens causing mass mortality in both farmed and wild populations. In this study, we confirmed that a novel ranavirus was related to mass die‐offs of black‐spotted pond frogs (Rana nigromaculata) in Sichuan Province, China. Histological examination revealed marked degeneration or necrosis in parenchymatous organs, and intracytoplasmic inclusions can be observed in the liver and intestine cells. The virus was isolated from diseased tadpoles (tentatively named the virus as RNRV), and the ranavirus‐like particles could be observed in infected EPC cells by the electron microscope. The tadpoles challenged with the isolated virus displayed similar clinical symptoms and pathogenicity as those naturally infected. Physicochemical characteristics showed that it was sensitive to chloroform treatment, trypsin treatment, heating treatment, acidity and alkalinity. Biological characteristics showed that RNRV can induce cytopathic effect (CPE) in various fish cell lines and the optimum growth temperature is 25~28°C. In addition, the complete genome sequence of RNRV was determined (GenBank accession number MG791866) and analysed. The results showed that the genome of RNRV consists of 104,286 bp containing 55.2% GC content and 104 predicted ORFs were identified in the genome. Phylogenetic analysis of the complete genome revealed that RNRV should belong to the FV3‐like group in genus Ranavirus, and is more closely related to RGV and STIV. These studies confirmed that the RNRV was the causative agent of this natural epizootic event and genome analysis indicated that it belongs to the FV3‐like group. In addition, viral physicochemical and biological characteristics will provide a scientific basis for prevention and control. [ABSTRACT FROM AUTHOR]

Acinetobacter lwoffii, a serious human pathogen, has been identified as a cause of nosocomial infections such as bacteremia, pneumonia and meningitis. There are only a few studies reporting A. lwoffii as a pathogen of fish. During 2016 and 2017, six bacterial strains, isolated from diseased fish of the Schizothorax genus, were identified as A. lwoffii by morphology, biochemical tests, 16S rDNA and gyrB gene sequencing analysis. One of these isolates was selected for experimental infection of Sclizothorax prenanti, Schizothorax davidi and Schizothorax wangchiachii, to confirm its pathogenicity. Experimentally infected fish showed similar symptoms to those observed in fish after natural outbreaks. Susceptibility of the isolates to 14 antibiotics was tested using a disc diffusion method; all isolates were resistant to cephalothin, aminoglycosides and β-lactams, and sensitive only to some fluoroquinolones and tetracyclines. Histological examination revealed that A. lwoffii infection could cause pathological lesions in multiple organs and tissues, especially in liver, kidney, spleen and heart. These lesions included extensive haemorrhage, vacuolar degeneration, necrosis and inflammatory cell infiltration. To our knowledge, this is the first report on A. lwoffii as a virulent pathogen for fish of the Schizothorax genus., (© 2018 Blackwell Verlag GmbH.)