China is on the track tackling Enteromorpha spp forming green tide

Green tide management is supposed to be a long term fight rather than an episode during the 29th Olympic Games for China, since it has been gaining in scale and frequency during the past 3 decades in both marine and estuary environment all over the world. A number of rapid-responding studies including oceanographic comprehensive surveys along the coastline have been conducted during the bloom and post-bloom periods in 2008 by Chinese marine scientists. The preliminary results are as below: (1) phylogenetic analysis indicates that the bloom forming alga forms a clade with representatives of the green seaweed Enteromorpha linza, though, the alga has been identified as E. proliera by means of morphological; (2) the present data suggest that the bloom was originated from south of Yellow Sea, but not the severely affected area near Qingdao City; (3) pathways of reproduction for E. prolifera have approved to be multifarious, including sexual, asexual and vegetative propagation; (4) somatic cells may act as a propagule bank, which is supposed to be a very dangerous transmitting way for its marked movability, adaptability and viability; (5) pyrolysis of the alga showed that three stages appeared during the process, which are dehydration (18–20^o^C), main devolatilization (200–450^o^C) and residual decomposition (450–750^o^C), and activation energy of the alga was determined at 237.23 KJ•mol^-1^. Although the scarce knowlegde on E. prolifera not yet allow a fully understanding of the green tide, some of the results suggests possible directions in further green tide research and management

Simultaneous spectroscopic determination of trace mixed organic acids in aqueous samples using magnetic solid phase extraction coupled with chemometrics method

243-249The polyaniline-coated magnetite/silica nanomaterials (Fe3O4@SiO2/PANI) have been synthesized and successfully applied as an effective sorbent for preconcentration of several typical organic acids from environmental water samples. The properties of Fe3O4@SiO2/PANI are characterized by FT-IR and XPS. These magnetic materials can enrich trace organic acids effectively by solid-phase extraction. Three kinds of organic acids, including benzoic acids, phthalic acids, and p-toluene sulfonic acids, are selected as target analytes for magnetic solid phase extraction (MSPE). Various experimental parameters of the MSPE were investigated and optimized. After the desorption process, the elution is detected by the UV-visible spectrophotometer. The spectroscopic data are analyzed through the partial least squares (PLS) method, which facilitate quantitation of mixture from complex data. The enrichment factor of benzoic acids, phthalic acids and p-toluene sulfonic acids reached 19.53, 20.31, and 16.89, respectively. A wide measurement range of 10 μg L-1 to 50 mg L-1 is obtained. The LOD is 0.8 μg L-1. The spiked recoveries in the range of 94%-101% with RSD (n=8) lower than 4%. The results illustrated that the combined approach of MSPE and PLS has great applied potential for a mixture of trace compounds in different fields because of its high efficiency, easy to operate conditions, speediness, and simplicity

Modeling and Prediction of Coal Ash Fusion Temperature based on BP Neural Network

Coal ash is the residual generated from combustion of coal. The ash fusion temperature (AFT) of coal gives detail information on the suitability of a coal source for gasification procedures, and specifically to which extent ash agglomeration or clinkering is likely to occur within the gasifier. To investigate the contribution of oxides in coal ash to AFT, data of coal ash chemical compositions and Softening Temperature (ST) in different regions of China were collected in this work and a BP neural network model was established by XD-APC PLATFORM. In the BP model, the inputs were the ash compositions and the output was the ST. In addition, the ash fusion temperature prediction model was obtained by industrial data and the model was generalized by different industrial data. Compared to empirical formulas, the BP neural network obtained better results. By different tests, the best result and the best configurations for the model were obtained: hidden layer nodes of the BP network was setted as three, the component contents (SiO2, Al2O3, Fe2O3, CaO, MgO) were used as inputs and ST was used as output of the model

Modeling and Prediction of Coal Ash Fusion Temperature based on BP Neural Network

Coal ash is the residual generated from combustion of coal. The ash fusion temperature (AFT) of coal gives detail information on the suitability of a coal source for gasification procedures, and specifically to which extent ash agglomeration or clinkering is likely to occur within the gasifier. To investigate the contribution of oxides in coal ash to AFT, data of coal ash chemical compositions and Softening Temperature (ST) in different regions of China were collected in this work and a BP neural network model was established by XD-APC PLATFORM. In the BP model, the inputs were the ash compositions and the output was the ST. In addition, the ash fusion temperature prediction model was obtained by industrial data and the model was generalized by different industrial data. Compared to empirical formulas, the BP neural network obtained better results. By different tests, the best result and the best configurations for the model were obtained: hidden layer nodes of the BP network was setted as three, the component contents (SiO2, Al2O3, Fe2O3, CaO, MgO) were used as inputs and ST was used as output of the model

Simulation of circulating fluidized bed (CFB) boiler oxygen-enriched combustion

Conference Name:2nd International Conference on Energy, Environment and Sustainable Development, EESD 2012. Conference Address: Jilin, China. Time:October 12, 2012 - October 14, 2012.In this paper, we focus on the relationship between oxygen-enriched combustion efficiency and oxygen content of primary air under N2 /O2 atmosphere combustion on CFB boiler. Firstly, an entirely possible of CFB boiler oxygen-enriched combustion model was proposed. Secondly, a platform was built for simulation of CFB combustion process on XD-APC configuration software. Finally, industrial simulation with industrial data was going on to prove the platform was reasonable. The simulation results were consistent of industrial data. It shows the simulation platform reliability, and the model accuracy. On this basis, coal combustion efficiency was simulated. It shows that the combustion efficiency increases following by oxygen content increasing. It's economic for real process when oxygen content chooses from 25% to 30%. ? (2013) Trans Tech Publications, Switzerland

Long noncoding RNA microvascular invasion in hepatocellular carcinoma is an indicator of poor prognosis and a potential therapeutic target in gastric cancer

Background: Long noncoding RNAs (lncRNAs) have been shown to have a fundamental role in cancer initiation and development. LncRNA microvascular invasion in hepatocellular carcinoma (MVIH) has been identified as a potential prognostic marker in several cancers; however, its role in gastric cancer (GC) has not been elucidated. Materials and Methods: A total of 152 tissue samples from patients underwent GC surgical resection in Linyi People's Hospital between 2007 and 2010 were collected. Quantitative real-time polymerase chain reaction was conducted to examine the expression level of lncRNA MVIH. The selection of clinically important cut-off scores for MVIH expression was based on receiver operating characteristic curve analysis. Then, the association between MVIH and GC clinicopathological parameters was analyzed. Moreover, univariate and multivariate Cox regression analysis were performed to reveal the relationship between MVIH and GC prognosis. Results: GC tissues exhibited a higher lncRNA MVIH expression level than paired nontumoros tissues. High MVIH level was revealed to be associated with the T stage, tumor-node-metastasis (TNM) stage and lymphatic metastasis of GC. Specially, patients with high MVIH expression level showed significantly shorter overall survival rate and progression-free survival rate. Moreover, invasion depth, distant metastasis, TNM stage, and MVIH expression were identified as risk factors of GC poor prognosis on univariate Cox regression analyses. By further analyzing these factors with multivariate logistic regression, high MVIH, and distant metastasis were discovered to be independent risk factors of GC prognosis. Conclusions: High MVIH is an independent risk factor of GC prognosis. LncRNA MVIH may serve as a potential therapeutic target and a prognostic marker of GC patients

Construction of data resource sharing center of the Puguang Intelligent Gas Field

During the initial construction of the Puguang Gas Field, information infrastructure was built. Due to the absence of unified planning and deployment, however, many “isolated information islands” were formed in data systems, and the data resources cannot meet the construction requirements of intelligent gas field. In this paper, the status quo and problems of data resources in the Puguang Gas Field were analyzed, and a data resource sharing center was constructed according to the overall architecture design of the Puguang Intelligent Gas Field. Based on the architecture design of data resource sharing center, the overall construction conception of data resource sharing center was put forward and the business data model was designed. Finally, the integrated data collection, storage, calculation and utilization was realized by establishing data standard, combing data sources and designing data services, and then it was applied on site. The following research results were obtained. First, the data resource sharing center is an important foundation for the construction of this project, and its overall architecture is divided into three layers from bottom to top, i.e., data specification and standard, data collection, storage, calculation and utilization, and data control. Second, the data resource sharing center achieves the one-time collection, centralized storage, shared use and unified management of exploration & development, gathering & purification, production & operation and safety & environmental protection data, and provides an important data base for the construction of business system of the intelligent gas field and a comprehensive, reliable and effective data support for the intelligent and mobile application in the Puguang Gas Field. Keywords: Intelligent gas field, Puguang gas field, Standard and specification, Post data, Real time data, Video data, Distributed storage, Data sharing servic

High-Strength Double-Network Conductive Hydrogels Based on Polyvinyl Alcohol and Polymerizable Deep Eutectic Solvent

Conductive hydrogels feature the flexibility of soft materials plus conductive properties providing functionality for effectively sticking to the epidermis and detecting human activity signals. Their stable electrical conductivity also effectively avoids the problem of uneven distribution of solid conductive fillers inside traditional conductive hydrogels. However, the simultaneous integration of high mechanical strength, stretchability, and transparency through a simple and green fabrication method remains a great challenge. Herein, a polymerizable deep eutectic solvent (PDES) composed of choline chloride and acrylic acid was added to a biocompatible PVA matrix. The double-network hydrogels were then simply prepared by thermal polymerization and one freeze-thaw method. The introduction of the PDES significantly improved the tensile properties (1.1 MPa), ionic conductivity (2.1 S/m), and optical transparency (90%) of the PVA hydrogels. When the gel sensor was fixed to human skin, real-time monitoring of a variety of human activities could be implemented with accuracy and durability. Such a simple preparation method performed by combining a deep eutectic solvent with traditional hydrogels offers a new avenue to construct multifunctional conductive hydrogel sensors with excellent performance

Synchronization control scheme for multi-process systems based on model predictive control

Conference Name:2013 25th Chinese Control and Decision Conference, CCDC 2013. Conference Address: Guiyang, China. Time:May 25, 2013 - May 27, 2013.Multi-process system (MPS) is an important process system for modern industry. The parallel operating subsystems may have synchronization requirements. A generalized synchronization control scheme is thus developed in this paper based on the model predictive control framework by combining a generalized synchronization cost function and the predictive cost function. The resulted control algorithm indicates that the predictive control errors of each sub-process and the predictive synchronization errors between sub-processes are used together as feedback information in the control scheme to ensure the optimal control performances of each sub-processes as well as synchronization performance, which essentially leads to a multi-input and multi-output (MIMO) control for the MPS. With a proper selection of the synchronization error functions, ratio and distance synchronization controls are conducted with the numerical simulation on an MPS consists of three sub-processes. The results clearly prove the effectiveness, robustness and flexibility of the proposed synchronization control scheme. ? 2013 IEEE