Discrimination of different social companions in spectacled parrotlets (Forpus conspicillatus): evidence for individual vocal recognition

Individual recognition is generally assumed to be a prerequisite for establishing and maintaining a complex social system. Indeed, there is good evidence that highly social species have complex systems of vocal communication with individual recognition by acoustic cues. In this study, we provide experimental evidence that vocal class and individual recognition is present in a non-passerine bird, the spectacled parrotlet (Forpus conspicillatus). Spectacled parrotlets live in a complex system of social relationships. Soon after fledging, the young establish close sibling relationships which are important for successful socialization, pairing and reproduction. In a series of playback experiments we tested if spectacled parrotlets use contact calls for vocal recognition. The results showed that spectacled parrotlets discriminate between the contact calls of different social categories. Adult birds preferred to respond to the contact calls of their mates. Subadult individuals recognized the contact calls of their siblings. During the period of pair bond formation, the affiliative contacts to the siblings decrease, but the parrotlets continue to respond to the calls of their siblings. This is the first evidence that vocal sibling recognition might outlast the period of strong sibling interaction and extends into the period of pair bond formation. In cases of mate loss or divorce, the acoustic contact to their siblings might facilitate the re-establishment of close sibling relationships. Received: 29 October 1997 / Accepted after revision: 5 April 1998     

基于BERT-BILSTM-CRF模型的电力行业事故文本智能分析*

为解决电力行业事故报告文本较长、语义复杂,难以进行有效文本识别问题,提出1种以BERT作为底层的预训练模型,并设计1种双重注意力机制编码器,结合BILSTM-CRF深度挖掘事故文本语义特征,从而实现文本智能分析。首先构建电力词典,通过对BERT预训练,进行BIO标注,然后引入BILSTM-CRF模型实现对文本标签智能分类,最后将该模型与现行其他4种深度学习模型进行对比。研究结果表明:该模型智能识别精确率、召回率及F1值(查准率)均达到约97%,较其他4种模型中效果最好的模型分别提高0.02,0.03,0.02。研究结果可为电力行业事故报告文本分析提供1种新思路。     

分子识别作用下光催化降解偶氮染料酸性红GR

合成了β-环糊精(β-CD)与偶氮染料酸性红GR(ARGR)的包结物,并采用红外光谱仪对ARGR、β-CD及β-CD与ARGR的包结物进行了表征,表征结果显示,β-CD与ARGR的包结物的特征峰的峰形和强度与β-CD相似,但峰位有明显的偏移,说明ARGR进入了β-CD空腔与β-CD发生了分子识别作用。采用TiO2作为催化剂,研究了β-CD分子识别后ARGR的光催化降解行为,实验结果表明,在ARGR质量浓度为20.0 mg/L、β-CD浓度为1.8×10-5 mol/L、体系pH为4.0、TiO2加入量为1.0 g/L、光催化反应时间为60 min的条件下,经β-CD分子识别后ARGR的光催化降解率可达100%。     

模式识别在火灾调查中的汽油分类问题的应用研究

在火灾调查中,检测汽油成分并对其进行正确分类尤为重要.运用GC-MS对90#和93#两种普通汽油的共50个样本进行检测,所得的GC-MS原始数据通过PCA方法进行处理,以提取有用信息,避免冗余变量进入后续计算.在此基础上应用KNN方法对这两种汽油助燃剂进行分类.结果表明, KNN方法对这两种汽油的分类准确率达到100%,且当初始数据未经标准化预处理时也能达到同样准确的分类效果.研究表明:将模式识别方法正确地运用到助燃剂鉴定和分类工作中有助于火灾调查.     

浦阳江流域(浦江县段)面源污染模型估算及河流生态缓冲带重点区域识别

以浦阳江流域(浦江县段)为研究区,从流域面源污染空间特征入手,提出浦阳江流域岸边带建设的重点区域。采用DPeRS面源污染负荷估算模型,具体分析了2018年浦阳江流域面源污染负荷空间分布特征,并采用面向对象方法提取了岸线和河流生态缓冲带土地覆盖类型,以汇水区为单元,结合面源污染估算结果识别了浦阳江流域河流生态缓冲带重点区。结果表明：浦阳江流域中部和中北部地区面源污染排放负荷较高,面源污染入河负荷高值区主要集中于中下游地区;该流域31个汇水区中,TN和NH₄⁺-N重点汇水区有17个,主要分布在流域的中部和东北部;TP和COD重点汇水区有12个,集中分布于流域中部;浦阳江流域河流生态缓冲带范围内,植被类型和非植被类型面积占比分别为65.49%和34.51%,其中耕地面积占比29.36%,建筑用地占比11.89%;综合浦阳江流域面源污染重点汇水区和河流生态缓冲带现状遥感提取结果,筛选出的重点区包括下游地区的7号汇水区和中游地区的18~25号汇水区所在的河流生态缓冲带。今后,可针对其重点区域设计生态防护工程,也应结合源头减量、过程拦截、末端消纳与资源循环利用的防控策略,综合削减面源污染物入河量。     

A novel approach for VOC source apportionment combining characteristic factor and pattern recognition technology in a Chinese industrial area

Volatile organic compound (VOC) emission control and source apportionment in small-scale industrial areas have become key topics of air pollution control in China. This study proposed a novel characteristic factor and pattern recognition (CF-PR) model for VOC source apportionment based on the similarity of characteristic factors between sources and receptors. A simulation was carried out in a typical industrial area with the CF-PR model involving simulated receptor samples. Refined and accurate source profiles were constructed through in situ sampling and analysis, covering rubber, chemicals, coating, electronics, plastics, printing, incubation and medical treatment industries. Characteristic factors of n-undecane, styrene, o-xylene and propane were identified. The source apportionment simulation results indicated that the predicted contribution rate was basically consistent with the real contribution rate. Compared to traditional receptor models, this method achieves notable advantages in terms of refinement and timeliness at similar accuracy, which is more suitable for VOC source identification and apportionment in small-scale industrial areas.     

基于指标协调性的水体富营养化状况的模糊识别

在湖泊富营养化评价指标体系中,同一指标的分级界点值差异很大,近似地呈现几何级数变化,同时各指标权重的选择与内涵存在不确定性,基于这两种认识,构建基于指标协调性和模糊权下的湖泊水质评价模型。对评价标准及待评价水质监测值进行对数变换,运用层次分析法求出指标的模糊权重;以此构造隶属函数,按最大隶属原则来评判地表水质量等级。应用此模型对巢湖西半湖水体进行富营养化识别,得出结果与生态评估结果基本一致。     

应用属性识别模型评价洛阳市大气环境质量

通过将熵值法与属性识别理论相结合,建立了基于熵权的属性识别理论模型,并根据"大气环境质量标准"(GB3095-1996),对洛阳市2005年至2009年的大气环境质量进行了综合评价。结果表明:2005年至2009年洛阳市的大气环境质量均为Ⅱ级。评价结果与模糊数学综合评判法分析结果一致,说明运用属性识别理论应用于大气环境质量评价是合理可信的。     

城市大气污染物浓度预测模糊识别理论与模型

根据大气污染物的浓度具有模糊性且与多种指标相关的特点，提出对其进行预测的模糊识别理论与模型，并以二氧化硫为例，由２５个预测点大气中ＳＯ２浓度和相关指标的实测资料，利用上述理论与模型得出最优模糊预测参数，并对其它５个观测点的ＳＯ２浓度进行了预测检验。     

碧流河水库水质状况的模糊模式识别及对策讨论

提出了确定污染指标权重的新方法,运用陈守煜建立的模糊模式识别理论模型对大连市碧流河水库连续３ａ的水质进行了综合评价,并探讨了水质保护对策