Comparing Eight Computing Algorithms and Four Consensus Methods to Analyze Relationship between Land Use Pattern and Driving Forces

Although many computing algorithms have been developed to analyze the relationship between land use pattern and driving forces (RLPDF), little has been done to assess and reduce the uncertainty of predictions. In this study, we investigated RLPDF based on 1990, 2005 and 2012 datasets at two spatial scales using eight state-of-the-art single computing algorithms and four consensus methods in Jinjing rive catchment in Hunan Province, China. At the entire catchment scale, the mean AUC values were between 0.715 (ANN) and 0.948 (RF) for the single-algorithms, and from 0.764 to 0.962 for the consensus methods. At the subcatchment scale, the mean AUC values between 0.624 (CTA) and 0.972 (RF) for the single-algorithms, and from 0.758 to 0.979 for the consensus methods. At the subcatchment scale, the mean AUC values were between 0.624 (CTA) and 0.972 (RF) for the single-algorithms, and from 0.758 to 0.979 for the consensus methods. The result suggested that among the eight single computing algorithms, RF performed the best overall for woodland and paddy field;consensus method showed higher predictive performance for woodland and paddy field models than the single computing algorithms. We compared the simulation results of the best - and worst-performing algorithms for the entire catchment in 2012, and found that approximately 72.5% of woodland and 72.4% of paddy field had probabilities of occurrence of less than 0.1, and 3.6% of woodland and 14.5% of paddy field had probabilities of occurrence of more than 0.5. In other words, the simulation errors associated with using different computing algorithms can be up to 14.5% if a probability level of 0.5 is set as the threshold. The results of this study showed that the choice of modeling approaches can greatly affect the accuracy of RLPDF prediction. The computing algorithms for specific RLPDF tasks in specific regions have to be localized and optimized.

The unusual physicochemical properties of azulene and azulene-based compounds

Azulene,an isomer of naphthalene,has become one of hot chemical structures in the research field of functional materials,due to its anti-Kasha's rule emissions and unusual physicochemical properties(e.g.,photophysical,electrochemical,and photoelectrochemical properties).In the past,the synthesis of azulene-based compounds is relatively inconvenient.Recently,there have been more and more reports about the synthesis strategies of the azulene-based compounds for finely tuning the physicochemical properties.In this article,we introduce several synthetic methods for kinds of azulene-based compounds which has unusual physicochemical properties.With these convenient methods and unique physicochemical properties,azulene-based compounds can be applied into many fields such as specific bioimaging,advanced molecular switches,organic field-effect transistor(OFET),organic light emitting diode(OLED),solar cells,and so forth.And these properties are also summarized here.