近60年来印江河流域极端气候演变及其对净初级生产力和归一化植被指数的影响

极端气候事件的发生改变了区域水热条件,并影响着生态环境变化。然而,目前长时间尺度上极端气候的演变规律及其对生态环境的影响尚不明晰。采用Mann-Kendall趋势及突变检验法、连续小波变换和Hurst指数法揭示了喀斯特槽谷印江河流域极端气候的变化趋势、突变时间、周期性特征和未来演变规律,并利用Lindeman-Merenda-Gold模型定量评估了极端气候溶变对生态环境变化的影响。结果表明：(1)印江河流域极端气温显著上升,降雨量增多,呈现湿热多雨的气候特征。未来极端气温事件持续等级将更高,持续强度也更强。(2)同类型极端气候具有潜在的关联性,但不同类型极端气候间的影响较小,且多呈负相关。(3)印江河流域平均净初级生产力(NPP)和归一化植被指数(NDVI)在2000—2015年间呈现相反的变化趋势,NPP平均值为598.53 g C m^-2 a^-1,平均减少速率为-3.32 g C m^-2 a^-1。NDVI平均值为0.59,平均增长速率为0.0013/a。(4)冷持续指数(CSDI)、平均温差(D...     

Segmentation improvement through denoising of PET images with 3D-context modelling in wavelet domain

Positron emission tomography (PET) images have been incorporated into the radiotherapy process as a powerful tool to assist in the contouring of lesions, leading to the emergence of a broad spectrum of automatic segmentation schemes for PET images (PET-AS). However, not all proposed PET-AS algorithms take into consideration the previous steps of image preparation. PET image noise has been shown to be one of the most relevant affecting factors in segmentation tasks. This study demonstrates a nonlinear filtering method based on spatially adaptive wavelet shrinkage using three-dimensional context modelling that considers the correlation of each voxel with its neighbours. Using this noise reduction method, excellent edge conservation properties are obtained. To evaluate the influence in the segmentation schemes of this filter, it was compared with a set of Gaussian filters (the most conventional) and with two previously optimised edge-preserving filters. Five segmentation schemes were used (most commonly implemented in commercial software): fixed thresholding, adaptive thresholding, watershed, adaptive region growing and affinity propagation clustering. Segmentation results were evaluated using the Dice similarity coefficient and classification error. A simple metric was also included to improve the characterisation of the filters used for induced blurring evaluation, based on the measurement of the average edge width. The proposed noise reduction procedure improves the results of segmentation throughout the performed settings and was shown to be more stable in low-contrast and high-noise conditions. Thus, the capacity of the segmentation method is reinforced by the denoising plan used.     

Effects of homosynaptic depression on spectral properties of H-reflex recordings

The purpose of this study was to determine the effects of homosynaptic depression (HD) on spectral properties of the soleus (SOL) H-reflex. Paired stimulations, separated by 100?ms, were used to elicit an unconditioned and conditioned H-reflex in the SOL muscle of 20 participants during quiet standing. Wavelet and principal component analyses were used to analyze features of the time-varying spectral properties of the unconditioned and conditioned H-reflex. The effects of HD on spectral properties of the H-reflex signal were quantified by comparing extracted principal component scores. The analysis extracted two principal components: one associated with the intensity of the spectra and one associated with its frequency. The scores for both principal components were smaller for the conditioned H-reflex. HD decreases the spectral intensity and changes the spectral frequency of H-reflexes. These results suggest that HD changes the recruitment pattern of the motor units evoked during H-reflex stimulations, in that it not only decreases the intensity, but also changes the types of motor units that contribute to the H-reflex signal.     

Social forces can impact the circadian clocks of cohabiting hamsters

A number of field and laboratory studies have shown that the social environment influences daily rhythms in numerous species. However, underlying mechanisms, including the circadian system''s role, are not known. Obstacles to this research have been the inability to track and objectively analyse rhythms of individual animals housed together. Here, we employed temperature dataloggers to track individual body temperature rhythms of pairs of cohabiting male Syrian hamsters (Mesocricetus auratus) in constant darkness and applied a continuous wavelet transform to determine the phase of rhythm onset before, during, and after cohabitation. Cohabitation altered the predicted trajectory of rhythm onsets in 34% of individuals, representing 58% of pairs, compared to 12% of hamsters single-housed as ‘virtual pair’ controls. Deviation from the predicted trajectory was by a change in circadian period (τ), which tended to be asymmetric—affecting one individual of the pair in nine of 11 affected pairs—with hints that dominance might play a role. These data implicate a change in the speed of the circadian clock as one mechanism whereby social factors can alter daily rhythms. Miniature dataloggers coupled with wavelet analyses should provide powerful tools for future studies investigating the principles and mechanisms mediating social influences on daily timing.     

基于小波变换的土壤有机碳与其影响因子多尺度相关分析

基于GIS,采用小波变换和相关分析方法,以广东山区表层(0～20 cm)土壤有机碳密度及其影响因子(包括归一化植被指数NDVI、海拔、坡度和坡向)作为分析对象,选取4条样带,使用一维离散小波变换对分析对象进行多尺度分解,在栅格尺度上定量分析土壤有机碳密度与其影响因子相关关系的多尺度响应特征.结果表明: 研究区土壤有机碳密度与其影响因子具有不同程度的尺度相关性.NDVI在2、8和16 km尺度、海拔在8和16 km尺度下的控制作用最强;坡度的控制作用极弱,尺度相关性不显著;坡向在大于2 km尺度表现为随尺度增加而增大的负相关作用.不同样带的土壤有机碳密度受不同影响因子的制约,NDVI和海拔是影响广东山区土壤有机碳密度分布的主要因子,坡度和坡向仅在个别样带、较大尺度上起作用.     

Analysis and classification of compressed EMG signals by wavelet transform via alternative neural networks algorithms

We propose intelligent methods for classifying three different muscle types, i.e. biceps, frontallis and abductor pollicis brevis muscles, with low computational complexity. For this aim, electromyogram (EMG) signals are recorded and modelled by using an auto-regressive (AR) model. As the size of the EMG signals is usually large, the computational complexity of artificial neural network (ANN) systems drastically increases. Therefore, in the proposed scheme EMG signals are pre-processed by using a wavelet transform and then they are modelled by employing an AR approach. The AR coefficients are used to train and test the ANNs. Experimental results show that the highest achieved classification accuracy is more than 95% in the case of EMG signals pre-processed by wavelet transform. The wavelet transform-based pre-processing significantly increases the performance rates compared to standard multilayer perceptron and general regression neural networks algorithms.     

小波分析二点委夜蛾发生规律

二点委夜蛾Proxenus lepigone(Moschler),属鳞翅目夜蛾科,主要分布于日本、朝鲜、俄罗斯和欧洲等地。我国于2005年7月在河北省夏玉米田首次发现。近年来,该虫发生范围不断扩大,为害程度日益加重。2011年二点委夜蛾在我国夏玉米产区严重暴发,虫情涉及6省47市302个区(县),面积近220万hm2。山东省2007年首次在德州市发现该虫为害玉米,2011年全省17个地市普遍为害严重。为更准确地确定该虫的发生代次、每代各虫态发生历期、发生盛期、发生高峰日等信息,适时准确监控发生时期,本文采用symlets小波函数变换滤除高频信息,对山东省多地点二点委夜蛾成虫诱虫数据进行分析,结果显示,二点委夜蛾在山东省一年发生4代,越冬代、1代、2代、3代,始见蛾日在3月底—4月上旬,越冬代成虫发生期在3月底至4月上中旬,1代发生期在4月上旬至6月中下旬,2代发生期在6月中旬至8月上中旬,3代发生期在8月上旬至9月中下旬,越冬代幼虫发生期在9月中旬至10月中下旬,10月下旬左右老熟幼虫做茧越冬。另外,通过调查和室内观察还发现高温环境不利于二点委夜蛾幼虫生长发育,7—8月份高温期,成虫致畸率较高。     

The return of the vole cycle in southern Finland refutes the generality of the loss of cycles through ‘climatic forcing’

Multiannual cycles in the abundance of voles and other animals have been collapsing in the last decades. It has been proposed that this phenomenon is ‘climatically forced’ by milder winters. We here consider the dynamics of bank and field voles during more than two decades in two localities (170 km apart) in southern Finland. Using wavelet analysis, we show that a clear 3‐year cycle disappeared in the mid 1990s. However, the vole cycle returned in both localities after about 5 years despite winters becoming increasingly milder. In both localities, vole cycles were mainly determined by bank voles after the period of noncyclic dynamics, whereas field voles were dominant before this irregularity. Wavelet coherency analysis shows that spatial synchrony temporarily broke down during the period of noncyclic dynamics, but was fully restored afterwards. The return of the cycle despite ongoing rapid climate change argues against ‘climatic forcing’ as a general explanation for loss of cycles. Rather, the population‐dynamical consequences of climate change may be dependent on the local species composition and mechanism of delayed density dependence.     

大鼠慢波睡眠和睡眠过渡期脑电信号的小波变换分析

EEG信号经常包含许多快速的时变信息 ,将较长时间段的EEG信号近似看作平稳信号 ,进行FFT谱估计 ,存在其局限性。应用多分辨率小波变换方法 ,在频域和时域上可以同时定位分析大鼠慢波睡眠和睡眠过渡期脑电的动态变化特性。采用慢性埋植电极记录自由活动大鼠的皮层脑电 ,将信号用小波变换分解成δ、θ、α和 β四个分量 ,求各分量的功率和功率百分比的时间变化曲线 ,并与FFT功率谱分析结果进行比较。结果表明 :慢波睡眠期EEG中有 2 6 .2 %± 7.7%的时间段上δ分量功率小于总功率的 5 0 % ,且δ分量较大时 ,其他分量较小 ;δ分量较小时 ,其他分量较大 ,差别显著。此结果揭示了δ节律与θ和α节律之间的一种互补关系。而传统的FFT功率谱分析方法只能显示δ分量为主 (占总功率 70 .6 %± 6 .4 % )的功率谱 ,不能提供时变信息。对于睡眠过渡期的非稳态EEG信号 ,利用小波变换分解得到的θ和α分量可以鉴别出睡眠纺锤波 ,计算睡眠纺锤波的平均持续时间 ,并比较纺锤波和非纺锤波时期各个频谱分量的变化情况。由此可见 ,小波变换可用于计算新的EEG时频定量分析指标用于分析生理、病理和药理作用引起的睡眠EEG的变化过程 ,以弥补传统FFT功率谱分析的不足之处     

Fatigue-induced changes in muscle fiber action potentials estimated by wavelet analysis

We aimed to investigate fatigue-induced changes in the spectral parameters of slow (SMF) and fast fatigable muscle fiber (FMF) action potentials using discrete wavelet (DWT) and fast Fourier (FFT) transforms. Intracellular potentials were recorded during repetitive stimulation of isolated muscle fibers immersed in Ca²⁺-enriched medium, while extracellular potentials were obtained from muscle fibers pre-exposed to electromagnetic microwaves (MMW, 2.45 GHz, 20 mW/cm²). The changes in the frequency distribution of the action potentials during the period of uninterrupted fiber activity were used as criteria for fatigue assessment. The wavelet coefficients’ changes in the calculated frequency scales demonstrated a contribution of the increased [Ca²⁺]₀ to an earlier compression of the frequency spectrum towards lower ranges. Root mean square (RMS) analysis of the wavelet coefficients calculated from SMF potentials showed a reduction of the higher frequencies (scale 1) by 90% in elevated [Ca²⁺]₀ vs. 55% in controls and an increase of low frequencies (scale 5) by 323% vs. 187%, respectively. For FMF potentials a decrease of 71% vs. 59% for high frequencies (scale 1, elevated [Ca²⁺]₀ vs. control) and an increase of 386% vs. 295% in scale 5, respectively, were observed. MMW pre-exposure resulted in increased muscle fiber resistance to fatigue. The fatigue-induced decrease of potential high frequencies (SMF: 59% vs. 96%, MMW vs. control; FMF: 30% vs. 92%, respectively), and the increase of low frequencies (SMF: 200% vs. 207%, MMW vs. control; FMF: 93% vs. 314%, respectively) were significantly smaller and delayed in exposed muscle fibers. Data from RMS analysis indicate that DWT provides a reliable method for estimation of muscle fatigue onset and progression.