Population dynamics of Anarsia lineatella in relation to crop damage and the development of economic injury levels

Developing a relationship between pest abundance and damage to crops is essential for the calculation of economic injury levels (EILs) and to anticipate informed management decisions. Field studies were conducted for three successive years (2005, 2006 and 2007) in peach orchards of northern Greece to examine relationships between densities of Anarsia lineatella Zeller (Lepidoptera: Gelechiidae) populations and peach (Prunus persica) yields. According to a linear regression model, the increase in moth’s densities during the 1st flight resulted in a significant reduction in yield (y = 0.436x + 10.22, R² = 0.635, d.f. = 2,11, P < 0.05). Correlation of male moths captured during the 2nd flight and observed yield loss was significant (y = 0.5231x + 17.204, R² = 0.792, d.f. = 2,11, P < 0.05). Moreover, according to a linear model by counting the number of shoot strikes, during the first observation period, a forthcoming yield loss can be estimated (y = 27.389x?6.304, R² = 0.711, d.f. 2,11, F = 22.09, P < 0.05). A significant relationship was observed between the numbers of the 2nd generation larvae and yield loss (y = 163x, R² = 0.890). Regression coefficient of the above function represents yield loss per pest and was applied in the calculation of EIL’s and fixed Economic thresholds (ET’s). In addition, parameter of the price commodity was estimated for 2009 by applying stochastic autoregressive moving average model. By integrating above information, EIL and fixed ET estimated as 112 larvae and 84 larvae per sampling unit for a mean value (€4/0.1 ha) of cost management tactics and a 90% efficacy.     

Non-invasive diagnosis methods of coronary disease based on wavelet denoising and sound analyzing

The heart sound is the characteristic signal of cardiovascular health status. The objective of this project is to explore the correlation between Wavelet Transform and noise performance of heart sound and the adaptability of classifying heart sound using bispectrum estimation. Since the wavelet has multi-scale and multi-resolution characteristics, in this paper, the heart sound signal with different frequency ranges is decomposed through wavelet and displayed on different scales of the resolving wavelet result. According to distribution features of frequency of heart sound signals, the interference components in heart sound signal can be eliminated by selecting reconstruction coefficients. Comparing de-noising effects of four wavelets which are haar, db6, sym8 and coif6, the db6 wavelet has achieved an optimal denoising effect to heart sound signals. The de-noising result of contrasting different layers in the db6 wavelet shows that decomposing with five layers in db6 provide the optimal performance. In practice, the db6 wavelet also shows commendable denoising effects when applying to 51 clinical heart signals. Furthermore, through the clinic analyses of 29 normal signals from healthy people and 22 abnormal heart signals from coronary heart disease patients, this method can fairly distinguish abnormal signals from normal signals by applying bispectrum estimation to denoised signals via ARMA coefficients model.     

溧阳马尾松年轮与当地作物产量之间关系的初步研究

江苏溧阳的马尾松（ＰｉｎｕｓｍａｓｓｏｎｉａｎａＬａｍｂ）年轮年表与当地农作物产量间关系的分析表明,作物产量的波动系数可用马尾松年轮年表前一年年轮指数的非线性回归方程来描述,根据该回归方程计算的过去１１６年的作物产量系数与有关气象灾害文献的历史记载相吻合;同时发现该作物产量系数具一定的周期,因此采用滑动自回归（ＡＲＭ）模型对未来１０年（１９９１～２０００年）作物产量的波动情况进行了预测。     

Forecasting spore concentrations: A time series approach

Fungal basidiospores andCladosporium spores are the two most numerous spore types in the air of Dublin and its surroundings. They are known to have allergenic components, and the aim of the study described here is to develop a predictive model for these spores. A very simple model, which combines an estimated diurnal rhythm with a simple, one-parameter time series model, provided golld short-term forecasts. The one-step prediction error variance was reduced by 88% forCladosporium spores and by 98% for basidiospores.