Multiple song repertoire characteristics in the willow warbler (Phylloscopus trochilus): correlations with female choice and offspring viability

Male willow warblers have song repertoires which vary in complexity along several dimensions. We examined whether female choice, as measured by date of pairing, was based on these song characteristics in 4 different years. Pairing date was negatively correlated with song repertoire size in 1 year, and with song versatility in another year, but there was no consistent effect of any song characteristic on pairing throughout the years or in the pooled sample. The variable that best explained how soon a male pairs is male arrival date (only males that had settled territories before the first female arrived were considered in the analysis). This correlation is consistently significant in all years. This is most parsimoniously interpreted as females choosing some habitat characteristic in the same way that males do. A small percentage of males (8.3%) attracted and paired with a second female. The likelihood of becoming polygynous was not explained by any measured song characteristic, but it was related to arrival date: early males were more likely to pair with two females. Males with large repertoires fledged more young in their primary nests, and there was a trend for the offspring of these males to have a greater probability of being recruited into the population. In conclusion, the results show that in most years there is no sexual selection by female preference on song characteristics, although the data on reproductive success is consistent with the idea of repertoire size being an indicator of male quality. Received: 4 June 1999 / Received in revised form: 1 December 1999 / Accepted: 31 December 1999     

阳澄湖水源中典型嗅味物质测定与来源分析

以阳澄湖水源为研究对象,采用固相微萃取-气质联用法测定水中2-甲基异莰醇(2-MIB)、土臭素(GSM)、2,4,6-三氯苯甲醚(2,4,6-TAC)、2,3,4-三氯苯甲醚(2,3,4-TAC)、2,3,6-三氯苯甲醚(2,3,6-TAC)、2-异丙基-3甲氧基吡嗪(IPMP)、2-异丁基-3甲氧基吡嗪(IBMP)、...     

Development of categorical mapping for quantitative assessment of eutrophication

Spatial distribution of nutrient and phytoplankton variables is often illustrated using categorical mapping for each variable. However, the assessment of eutrophication cannot be derived from a single parameter since a synthesis of the environmental variables related to eutrophication is required. These shortcomings are further complicated since it is difficult to discriminate between distinct trophic states along natural environmental gradients. In the present work, a methodological procedure for quantitative assessment of eutrophication at a spatial scale was examined in the Gulf of Saronicos, Greece, based on a thematic map generated from the synthesis of four variables characterising eutrophication. The categorical map of each variable was developed using the Kriging interpolation method and four trophic levels were indicated (eutrophic, upper-mesotrophic, lower-mesotrophic and oligotrophic) based on nutrient and phytoplankton concentration scaling. Multi-criteria choice methods were applied to generate a final categorical map showing the four trophic levels in the area. This synthesis of categorical maps for assessing eutrophication at a spatial scale is proposed as a methodological procedure appropriate for coastal management studies.     

太湖叶绿素a浓度分布的时空特征及其影响因素

基于2005—2009年20次太湖采样期间的水质监测数据,研究了太湖叶绿素a浓度的主要分布特征,分析了水环境因子对叶绿素a浓度分布的季节性和空间性影响.结果表明,太湖叶绿素a浓度分布的空间差异较大,主要表现为梅梁湾、竺山湾、太湖西部和西南部湖区为叶绿素a浓度距平经验正交分解(EOF)第一模态空间分布的显著正值区,太湖湖心和东南湖区则为负值区;影响叶绿素a浓度的因子有水温、溶解氧、总氮、磷酸根和总磷,但总磷和水温的影响相对更为显著,而各季节叶绿素a浓度的影响因子则略有差异;影响藻类生长的因子存在较大的空间分布差异,但总磷、水温和溶解氧是其主要限制性因子,氮类营养盐的影响则处于次要地位.     

Stepwise multiple regression method of greenhouse gas emission modeling in the energy sector in Poland

The energy sector in Poland is the source of 81% of greenhouse gas (GHG) emissions. Poland, among other European Union countries, occupies a leading position with regard to coal consumption. Polish energy sector actively participates in efforts to reduce GHG emissions to the atmosphere, through a gradual decrease of the share of coal in the fuel mix and development of renewable energy sources. All evidence which completes the knowledge about issues related to GHG emissions is a valuable source of information. The article presents the results of modeling of GHG emissions which are generated by the energy sector in Poland. For a better understanding of the quantitative relationship between total consumption of primary energy and greenhouse gas emission, multiple stepwise regression model was applied. The modeling results of CO₂ emissions demonstrate a high relationship (0.97) with the hard coal consumption variable. Adjustment coefficient of the model to actual data is high and equal to 95%. The backward step regression model, in the case of CH₄ emission, indicated the presence of hard coal (0.66), peat and fuel wood (0.34), solid waste fuels, as well as other sources (-0.64) as the most important variables. The adjusted coefficient is suitable and equals R² = 0.90. For N₂O emission modeling the obtained coefficient of determination is low and equal to 43%. A significant variable influencing the amount of N₂O emission is the peat and wood fuel consumption.     

Stepwise multiple regression method of greenhouse gas emission modeling in the energy sector in Poland

The energy sector in Poland is the source of 81% of greenhouse gas (GHG) emissions. Poland, among other European Union countries, occupies a leading position with regard to coal consumption. Polish energy sector actively participates in efforts to reduce GHG emissions to the atmosphere, through a gradual decrease of the share of coal in the fuel mix and development of renewable energy sources. All evidence which completes the knowledge about issues related to GHG emissions is a valuable source of information. The article presents the results of modeling of GHG emissions which are generated by the energy sector in Poland. For a better understanding of the quantitative relationship between total consumption of primary energy and greenhouse gas emission, multiple stepwise regression model was applied. The modeling results of CO₂ emissions demonstrate a high relationship (0.97) with the hard coal consumption variable. Adjustment coefficient of the model to actual data is high and equal to 95%. The backward step regression model, in the case of CH₄ emission, indicated the presence of hard coal (0.66), peat and fuel wood (0.34), solid waste fuels, as well as other sources (− 0.64) as the most important variables. The adjusted coefficient is suitable and equals R² = 0.90. For N₂O emission modeling the obtained coefficient of determination is low and equal to 43%. A significant variable influencing the amount of N₂O emission is the peat and wood fuel consumption.     

Effects of mobile phone use on driving performance in a multiresource workload scenario

Objective: This study explores the influence of mobile phone secondary tasks on driving from the perspective of visual, auditory, cognitive, and psychomotor (VACP) multiple resource theory, and it is anticipated to benefit the human-centered design of mobile phone use while driving.

Methods: The present study investigated 6 typical phone use scenarios while driving and analyzed the effects of phone use distractions on driving performance. Thirty-six participants were recruited to participate in this experiment. We abandoned traditional secondary tasks such as conversations or dialing, in which cognitive resources can become interference. Instead, we adopted an arrow secondary task and an n-back delayed digit recall task.

Results: The results show that all mobile phone use scenarios have a significant influence on driving performance, especially on lateral vehicle control. The visual plus psychomotor resource occupation scenario demonstrated the greatest deterioration of driving performance, and there was a significant deterioration of driving speed and steering wheel angle once the psychomotor resource was occupied.

Conclusions: Phone use distraction leads to visual, cognitive, and/or motor resource functional limitations and thus causes lane violations and traffic accidents.     

Analysis of motorcycle accidents using association rule mining-based framework with parameter optimization and GIS technology

IntroductionAnalyzing key factors of motorcycle accidents is an effective method to reduce fatalities and improve road safety. Association Rule Mining (ARM) is an efficient data mining method to identify critical factors associated with injury severity. However, the existing studies have some limitations in applying ARM: (a) Most studies determined parameter thresholds of ARM subjectively, which lacks objectiveness and efficiency; (b) Most studies only listed rules with high parameter thresholds, while lacking in-depth analysis of multiple-item rules. Besides, the existing studies seldom conducted a spatial analysis of motorcycle accidents, which can provide intuitive suggestions for policymakers. Method: To address these limitations, this study proposes an ARM-based framework to identify critical factors related to motorcycle injury severity. A method for parameter optimization is proposed to objectively determine parameter thresholds in ARM. A method of factor extraction is proposed to identify individual key factors from 2-item rules and boosting factors from multiple-item rules. Geographic information system (GIS) is adopted to explore the spatial relationship between key factors and motorcycle injury severity. Results and conclusions: The framework is applied to a case study of motorcycle accidents in Victoria, Australia. Fifteen attributes are selected after data preprocessing. 0.03 and 0.7 are determined as the best thresholds of support and confidence in ARM. Five individual key factors and four boosting factors are identified to be related to fatal injury. Spatial analysis is conducted by GIS to present hot spots of motorcycle accidents. The proposed framework has been validated to have better performance on parameter optimization and rule analysis in ARM. Practical applications: The hot spots of motorcycle accidents related to fatal factors are presented in GIS maps. Policymakers can refer to those maps straightforwardly when decision making. This framework can be applied to various kinds of traffic accidents to improve the performance of severity analysis.     

判别符合率递增法辅助酚类化合物构效关系研究

计算了酚类化合物的分子连接性指数及其在正辛醇和水之间的分配系数ｌｏｇＰ，运用新近提出的数学方法－判别符合率递增法，对酚类化合物的构效关系进行了研究，所得结果优于逐步判别法及穷举法。     

Genetic amniocentesis in multiple gestations

Thirty-one genetic amniocenteses involving multiple gestations were performed in the genetics unit between 1976 and 1982. Three sets of triplets were included. Precise locations of the sacs were determined using real-time ultrasonography and successful sampling of all sacs was accomplished. Spontaneous abortions occurred in two normal twins and one normal triplet gestation. Two therapeutic abortions were performed for fetal abnormalities. Two cases of discordance for trisomy 21 (one twin and one triplet) were allowed to continue; the twin case terminated at 25 weeks' gestation with neonatal deaths and the triplets are alive and well.