Optimization on emergency materials dispatching considering the characteristics of integrated emergency response for large-scale marine oil spills

Many governments have been strengthening the construction of hardware facilities and equipment to prevent and control marine oil spills. However, in order to deal with large-scale marine oil spills more efficiently, emergency materials dispatching algorithm still needs further optimization. The present study presents a methodology for emergency materials dispatching optimization based on four steps, combined with the construction of Chinese oil spill response capacity. First, the present emergency response procedure for large-scale marine oil spills should be analyzed. Second, in accordance with different grade accidents, the demands of all kinds of emergency materials are replaced by an equivalent volume that can unify the units. Third, constraint conditions of the emergency materials dispatching optimization model should be presented, and the objective function of the model should be postulated with the purpose of minimizing the largest sailing time of all oil spill emergency disposal vessels, and the difference in sailing time among vessels that belong to the same emergency materials collection and distribution point. Finally, the present study applies a toolbox and optimization solver to optimize the emergency materials dispatching problem. A calculation example is presented, highlighting the sensibility of the results at different grades of oil spills. The present research would be helpful for emergency managers in tackling an efficient materials dispatching scheme, while considering the integrated emergency response procedure.Peer ReviewedPostprint (published version

Route Restoration Method for Sparse Taxi GPS trajectory based on Bayesian Network

In order to improve the availability of taxi GPS big data, we restore the chosen route for the sparse taxi GPS trajectory in this work. A trajectory restoration method based on Bayesian network is proposed. Compared with the traditional research solely based on time-spatial variables, this method additionally considers the characteristics of empty/heavy taxi status, weather conditions, drivers, vehicle running and other factors to carry out route restoration. A field case of grid network in Ningbo is taken to verify the applicability of the method, using the taxi GPS trajectory data from Ningbo Taxi Information Management Platform. The case results show that the accuracy of Bayesian network method based on multiple factors reaches 91.4%. Its performance is superior to the Multivariate logistic regression model. In addition, the proposed method is especially suitable for scenarios with a high missing rate of track data, such as a scene with timespan of about 5 min between neighbour trajectories

Graphene oxide-supported gold nanocomposites for highly sensitive sandwich immunosensor for α-fetoprotein detection

A graphene oxide-Au NPs sensor platform combined with a multiple-enzyme labeled detection antibody-carbon sphere bioconjugate has been used as the basis for an ultrasensitive electrochemical immunosensor to detect the cancer biomarker, α-fetoprotein (AFP). Greatly enhanced sensitivity has been achieved by using the bioconjugates featuring horseradish peroxidase (HRP) and Ab2 linked to carbon nanospheres (Ab2-HRP-Au-PDA-carbon sphere) at a high ratio of HRP/Ab2. After a sandwich immunoreaction, the Ab2-HRP-Au-PDA-carbon sphere captured onto the electrode surface produces an amplified electrocatalytic response due to the reduction of enzymatically oxidized thionine in the presence of hydrogen peroxide. The increase of response current is proportional to the AFP concentration in the range of 0.01-20 ng/mL, with the detection limit of 3 pg/mL. This amplification strategy is a promising platform for detection of other proteins and clinical applications

Bidirectional End-to-End Learning of Retriever-Reader Paradigm for Entity Linking

Entity Linking (EL) is a fundamental task for Information Extraction and Knowledge Graphs. The general form of EL (i.e., end-to-end EL) aims to first find mentions in the given input document and then link the mentions to corresponding entities in a specific knowledge base. Recently, the paradigm of retriever-reader promotes the progress of end-to-end EL, benefiting from the advantages of dense entity retrieval and machine reading comprehension. However, the existing study only trains the retriever and the reader separately in a pipeline manner, which ignores the benefit that the interaction between the retriever and the reader can bring to the task. To advance the retriever-reader paradigm to perform more perfectly on end-to-end EL, we propose BEER$^2$, a Bidirectional End-to-End training framework for Retriever and Reader. Through our designed bidirectional end-to-end training, BEER$^2$ guides the retriever and the reader to learn from each other, make progress together, and ultimately improve EL performance. Extensive experiments on benchmarks of multiple domains demonstrate the effectiveness of our proposed BEER$^2$.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

De novo transcriptome sequencing in Frankliniella occidentalis to identify genes involved in plant virus transmission and insecticide resistance

AbstractThe western flower thrips (WFT), Frankliniella occidentalis, a world-wide invasive insect, causes agricultural damage by directly feeding and by indirectly vectoring Tospoviruses, such as Tomato spotted wilt virus (TSWV). We characterized the transcriptome of WFT and analyzed global gene expression of WFT response to TSWV infection using Illumina sequencing platform. We compiled 59,932 unigenes, and identified 36,339 unigenes by similarity analysis against public databases, most of which were annotated using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Within these annotated transcripts, we collected 278 sequences related to insecticide resistance. GO and KEGG analysis of different expression genes between TSWV-infected and non-infected WFT population revealed that TSWV can regulate cellular process and immune response, which might lead to low virus titers in thrips cells and no detrimental effects on F. occidentalis. This data-set not only enriches genomic resource for WFT, but also benefits research into its molecular genetics and functional genomics

In situ synthesis and characterization of Prussian blue nanocubes on graphene oxide and its application for H2O2 reduction

An effective and facile in situ electroless deposition approach has been developed for growing high-quality Prussian blue nanocubes on the surface of graphene oxide (PBNCs/GO) in a controlled manner. The resulting hybrids are characterized by scanning electron microscopy, transmission electron microscopy, Fourier transform infrared, ultraviolet visible, X-ray diffraction and electrochemical techniques. The electrochemical behavior on the modified electrode is discussed in detail. A linear calibration of the biosensor is obtained in the range of 0.002–2.8 mM with a detection limit of 0.48 µM. The response is within less than 5 s and the detection sensitivity is 2502 µA mM-1cm-2. The proposed approach allows simple and controlled preparation of transition metal hexacyanoferrate nanocrystals/graphene oxide and is promising for the study of unique shape-, size-, and structure- dependent properties for optoelectronic, magnetic, and electrocatalytic applications.