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H. N. Cheng Catrina Ford Francis J. Kolpak Qinglin Wu 《Journal of Polymers and the Environment》2018,26(10):4114-4123
Although hemicellulose is found widely in nature, it is currently under-utilized as a raw material for commercial applications. It would be desirable to find new uses for hemicellulose in order to add value to this agro-based material. A common type of hemicellulose is xylan, which is found in a number of wood species and in cotton. In this work we prepared cationic and anionic xylan derivatives and characterized them by 13C NMR, FT-IR, size exclusion chromatography (SEC), thermal analysis, and rheology. In particular, the 13C NMR spectra of carboxymethyl xylan (CMX) and quaternary ammonium-adducted xylan (QAX) were fully assigned with the help of samples with different degrees of substitution. SEC indicated that the beechwood xylan showed a bimodal molecular weight distribution, but with derivatization the distribution tended to become unimodal. Thermal analysis and rheology studies did not uncover any surprises; the solution of xylan and its derivatives exhibited mostly Newtonian behavior. The blends of CMX and QAX produced a precipitate at almost all ratios, indicating the formation of a polyelectrolyte complex. When cationic and anionic xylan samples were added together to paper, the paper dry strength increased. Thus, the combination of cationic/anionic xylan may be of interest in selected applications. 相似文献
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Biomass is one of the renewable energy sources on which policy makers are greatly dependent on since it is a flexible feedstock capable of conversion into electricity, transport liquid fuels and heat by chemical and biological processes on demand. Though numerous publications have examined the relationship of economic growth with renewable energy and other parameters, biomass energy has never been included in these studies. Then, this study examines the causal relationship within a multivariate panel cointegration/error correction framework which combines the cross-section and time series data while allowing for heterogeneity across different provinces. After employing panel data regression model ranging from 2003 through 2012 to examine the relationships of biofuels production with sustainable development in China, the paper concludes that the development of biofuel energy production integrated with the consideration of the improvement of income per capita, and the attraction of more capital investment, does make a significant contribution to economic growth. However, some negative side effects including the increase of greenhouse emissions and the decrease of marginal land still coexist with the economic development. Of course, the importance of these findings lies on their implications and their adoption on strategic policies. 相似文献
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Min-Yuan Cheng Yi-Hsu Ju Yu-Wei Wu Sylviana Sutanto 《International Journal of Green Energy》2016,13(15):1599-1607
Nowadays, biodiesel is used as one of the alternative renewable energy due to the increasing energy demand. However, optimum production of biodiesel still requires a huge number of expensive and time-consuming laboratory tests. To address the problem, this research develops a novel Genetic Algorithm-based Evolutionary Support Vector Machine (GA-ESIM). The GA-ESIM is an Artificial Intelligence (AI)-based tool that combines K-means Chaotic Genetic Algorithm (KCGA) and Evolutionary Support Vector Machine Inference Model (ESIM). The ESIM is utilized as a supervised learning technique to establish a highly accurate prediction model between the input--output of biodiesel mixture properties; and the KCGA is used to perform the simulation to obtain the optimum mixture properties based on the prediction model. A real biodiesel experimental data is provided to validate the GA-ESIM performance. Our simulation results demonstrate that the GA-ESIM establishes a prediction model with better accuracy than other AI-based tool and thus obtains the mixture properties with the biodiesel yield of 99.9%, higher than the best experimental data record, 97.4%. 相似文献
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René van der Wal Cheng Zeng Danny Heptinstall Kapila Ponnamperuma Chris Mellish Stuart Ben Advaith Siddharthan 《Ambio》2015,44(4):612-623
Analysis of satellite-telemetry data mostly occurs long after it has been collected, due to the time and effort needed to collate and interpret such material. Delayed reporting reduces the usefulness of such data for nature conservation where timely information about animal movements is required. To counter this problem, we present a novel approach which combines automated analysis of satellite-telemetry data with rapid communication of insights derived from such data. A relatively simple algorithm (based on radial and angular velocity calculated from fixes) allowed instantaneous detection of excursions away from settlement areas and automated calculation of home ranges on the remaining data. Automating the detection of both excursions and home-range calculations enabled us to disseminate ecological insights from satellite-tag data instantaneously through a dedicated web portal. The automated analysis, interpretation, and communication of satellite-tag and other ecological data offer clear benefits to nature conservation research and practice. 相似文献
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不同培养条件下锰过氧化物酶(MnP)的合成及其对甲基橙的降解 总被引:1,自引:0,他引:1
高效、大规模、低成本合成木质素降解酶是直接采用其降解难降解有机污染物所必须解决的问题.对锰过氧化物酶(MnP)降解甲基橙和在非灭菌的反应器中连续合成MnP的可行性进行考察.结果表明,在采用2 mmol H2O2和1.5 mmol MnSO4的降解体系中,获最大脱色效果,且100、200和300 U/L的MnP可在8h内将甲基橙分别脱色18%、23%和35%;在非灭菌的反应器水平上实现了固定化培养的P.chrysosporium连续23 d合成MnP,但MnP酶活仅为2~ 23 U/L,难以酶解甲基橙;然而,在摇瓶培养条件下固定化的P.chrysosporium合成的MnP却能达1 152 U/L.因此,直接采用MnP对污染物进行降解以及在非灭菌的反应器中持续合成MnP是可行的,但就在非灭菌条件下如何提高MnP的合成量还有待开展深入的研究. 相似文献
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