Noise helped manifestation of intrinsic frequency: A case study in the mesoscopic hormone signaling system

The selective sustainment of nonlinear systems to signals is of great significance to signal transduction in living systems. We take hormone signaling as an example, and investigate the sustainment of internal and external signals. Simulation results prove that signals with "intrinsic frequency", no matter if it is noise induced or external injected, can be selectively sustained by exploiting internal and/or external noise. Both the internal and external noise can optimize the noise-induced signals, and the optimization is rather robust to the disturbance of external signals with other frequencies. These results are of significance for weak signal detection and trausduction in the presence of external signals.     

气候变化与玉米生产的响应分析——以1961-2010年开封市玉米生产为例

采用1961-2010年开封市气象资料、玉米产量资料、农作物受灾资料,分析气候变化对玉米产量的响应.结果表明:在此期间开封市玉米生长期积温与玉米产量均呈上升趋势,二者有明显的正相关关系,积温是气象因子影响玉米产量的主要因素;降水量与玉米产量呈正相上升关系,分析表明开封市玉米生长期的降水量多于玉米生长所需的水分;日照时数...     

基于改进型振子差分的微弱正弦信号检测

在信息检测领域,微弱信号检测是目前的研究热点之一.为了检测更低信噪比下的纳伏级微弱正弦信号,综合考虑混沌系统检测信号的灵敏度和工作稳定性2方面,建立了改进型双振子差分检测模型.通过振子差分对相空间中的周期部分和共模噪声的抑制特性,利用差分波形图检测微弱正弦信号.仿真实验结果表明:改进型的差分振子可以更好地对微弱正弦信号进行检测,且该方法具有稳定性高、灵敏度高、直观、易于实现等优点.     

微弱振动信号的谐波小波频域提取

为解决设备故障检测和故障预报中某些微弱振动信号难以提取出来的问题,在介绍谐波小波变换的优良特性及其基本原理的基础上,给出了谐波小波变换的实现技术.在不减少信息点数的情况下,用谐波小波变换成功地对微弱振动信号实现了频域提取与时域重构,并且实现了强噪声下微弱周期振动信号的频域提取.通过算例和工程实例,说明谐波小波方法在微弱信号的频域提取能力和精度上明显优于基于二进分解的小波方法和傅里叶分析方法,且在混有强噪声的信号提取中消除了二进小波包仍然存在的噪声泄漏,同时也显示了谐波小波变换的频域保相特性.     

Why large-scale climate indices seem to predict ecological processes better than local weather

Large-scale climatic indices such as the North Atlantic Oscillation are associated with population dynamics, variation in demographic rates and values of phenotypic traits in many species. Paradoxically, these large-scale indices can seem to be better predictors of ecological processes than local climate. Using detailed data from a population of Soay sheep, we show that high rainfall, high winds or low temperatures at any time during a 3-month period can cause mortality either immediately or lagged by a few days. Most measures of local climate used by ecologists fail to capture such complex associations between weather and ecological process, and this may help to explain why large-scale, seasonal indices of climate spanning several months can outperform local climatic factors. Furthermore, we show why an understanding of the mechanism by which climate influences population ecology is important. Through simulation we demonstrate that the timing of bad weather within a period of mortality can have an important modifying influence on intraspecific competition for food, revealing an interaction between climate and density dependence that the use of large-scale climatic indices or inappropriate local weather variables might obscure.     

The twentieth century was the wettest period in northern Pakistan over the past millennium

Twentieth-century warming could lead to increases in the moisture-holding capacity of the atmosphere, altering the hydrological cycle and the characteristics of precipitation. Such changes in the global rate and distribution of precipitation may have a greater direct effect on human well-being and ecosystem dynamics than changes in temperature itself. Despite the co-variability of both of these climate variables, attention in long-term climate reconstruction has mainly concentrated on temperature changes. Here we present an annually resolved oxygen isotope record from tree-rings, providing a millennial-scale reconstruction of precipitation variability in the high mountains of northern Pakistan. The climatic signal originates mainly from winter precipitation, and is robust over ecologically different sites. Centennial-scale variations reveal dry conditions at the beginning of the past millennium and through the eighteenth and early nineteenth centuries, with precipitation increasing during the late nineteenth and the twentieth centuries to yield the wettest conditions of the past 1,000 years. Comparison with other long-term precipitation reconstructions indicates a large-scale intensification of the hydrological cycle coincident with the onset of industrialization and global warming, and the unprecedented amplitude argues for a human role.     

基于非线性系统随机共振的多频弱信号检测

针对实际探测的弱信号常常是多个频率弱信号共存的的情形,进行了利用随机共振检测多频周期性弱信号的研究,以便把利用随机共振的弱信号检测应用于信息处理中微弱信息识别与提取。数值计算结果表明,在适当调节系统参数的情况下,强同频噪声下的多频周期性弱信号经过非线性双稳态系统后,相差不超过一个数量级的几个低于0.5Hz的不同频率的弱信号都可以同时发生随机共振而被检测出来,其信噪比改善十分明显,可以提高30dB以上。该方法在信息识别与信息处理方面具有潜在的应用价值。     

临夏盆地1.95MaBP的气候转型事件与青藏高原隆升作用于大气的临界高度

湖相地层孢粉分析的结果表明，临夏盆地在1．95MaB．P．前后发生过一次重要的气候转型事件。在此之前，南海热带季风信号在地层记录中存在较强的表现，在此之后热带季风信号减弱而高纬冰盖信号加强。CaCO3指标的周期分析同样表明，在1．95MaBP前后确实出现了气候的主导周期转型，在此之前，气候变化周期以类岁差的25kyr周期为主，而在此之后，以类倾角的38kyr周期为主。发生在临夏盆地1．95MaBP的这次气候转型事件表明青藏高原地面在当时隆升到一个可以改变周围地区大气环流的临界高度，如果以青藏高原在2．6MaB．P．- 0．6MaB．P．的平均抬升速率推算，这一临界高度可能在2500m左右。     

基于互相关算法的CSAMT接收信号处理研究

针对可控源音频大地电磁法（CSAMT: Controlled Source Audio-frequency Magnetotelluric）实际勘探中, 因深部目标体响应信号微弱, 测量环境噪声严重等特殊情况而导致接收信号的清晰度大大降低的问题, 提出一种基于互相关算法的CSAMT接收数据去噪处理的新方法。该方法利用发射信号与接收信号之间相关性强, 与随机噪声相关性弱的特点, 设计发射信号电流波形记录器, 将接收信号和发射信号作互相关处理, 滤掉噪声等干扰信号。实验结果表明, 该方法可压制噪声, 可提高CSAMT测量的准确性。     

大连地区的气候生产潜力分析

本文对大连地区主要作物的气候生产潜力进行了估算。气候生产潜力可划分为三个层次,即光能生产潜力,光温生产潜力和气候(光、温、水)生产潜力。计算结果表明:玉米的气候生产潜力可达到657～750公斤/亩,水稻可达到1300公斤/亩左右。并以气候生产力指数反映一地的气候生产力水平和光、温、水配合程度。     

基于自适应层数分解的小波变换滤除冲击信号

针对掺杂在冲击信号中的微弱振动信息被淹没的问题,提出了一种基于小波变换滤除冲击信号提取微弱振动信号的方法.该方法采用自适应层数分解的小波变换分析原理,根据冲击信号特征,合理选择小波基,对冲击信号进行分析滤除.为获得较好的滤除效果,针对分解层数的自适应性,提出了一种分解层数的自适应确定方法.对含有冲击干扰的微弱标准信号进行数值模拟,对含有冲击干扰的微弱金刚砂振动信号进行实测分析.结果表明该方法能自适应性地确定小波分解层数,并有效滤除冲击提取被淹没的微弱振动信号.     

高光效对吉林省玉米气候资源利用效率的影响

为研究在东北半干旱地区大田种植条件下,不同种植方式的玉米群体气候资源利用效率、干物质积累情况和产量等特征,为区域玉米高效栽培模式技术提供理论依据。2014—2016年,在吉林省公主岭市进行大田试验,选取先玉335为研究对象,通过田间对照试验方法,分别设置了垄向南偏西20°、种植间距为0.4～1.25 m的高光效和垄向南偏西20°的高光效小垄处理,研究了不同种植方式下玉米气候资源利用情况。结果表明：高光效处理与高光效小垄和对照比,有较高的气候资源利用效率,收获指数最高,产量最高,产量性状表现更好,抽穗之后的干物质积累速率更高。可见,高光效种植方式对于产量有提升作用;垄向调整和株行距共同作用对于干物质积累和雌穗性状有一定的影响,实际生产中可根据需求选择种植方式。     

微弱信号提取中的小波方法研究

针对于实际应用中的小信号特别是完全被噪声淹没情况下的微弱信号提取的问题，本文依据白噪声信号的小波变换系数相对比有用信号的小波系数小的特点，利用小波变换对信号进行消噪来提取微弱信号，仿真结果表明：小波变换能够有效的消除噪声，将有用微弱信号从受噪声污染的信号中提取出来。     

超混沌迭代同步在数字语音保密通讯中的应用

提出超混沌迭代系统的主动－被动（ＡＰＤ）同步方法,研究了它对语音的加、解密性能,证明此系统可以应用于数字语音保密通讯,并建立了计算机模拟超混沌迭代系统同步的数字语音加密解密系统,实现了混沌语音保密通讯．此方法具有同步速度快,恢复语音精度高,难于破译的特点     

Changes in the power spectrum of electrical signals in maize leaf induced by osmotic stress

To quantify the characteristics of the power spectrum of plant electrical signals, we defined the following concepts:spectral edge frequency (SEF), spectral center frequency (SCF), power index (PI) and power spectral entropy (PSE). These parameters were used to examine and quantify changes in the power spectrum of electrical signals in maize leaves under osmotic stress. In the absence of osmotic stress, the SEF of the electrical signal in maize leaves was approx. 0.2 Hz and the SCF was approx. 0.1 Hz. The electrical signal in maize leaves was mainly a slow wave signal with a frequency of 0-0.1 Hz. After 2 h osmotic stress, the SEF and SCF of the electrical signal increased to higher frequencies. The proportion of the fast wave frequency also increased to 0.1-0.2 Hz, resulting in a dramatic increase in PSE. We also found that the changes in PSE and SCF were significantly correlated during osmotic stress. We propose that the changes in the PSE and SCF in maize leaves can be used as a sensitive signal indicating water deficit in leaf cells under osmotic stress. Thus, measurement of SCF or PSE of electrical signals in maize leaves could be used to develop early warning and rapid diagnosis techniques for the water demands of plants.     

基于 FPGA 的微弱信号检测与实现技术

研究了杜芬混沌振子(Duffing chaos oscillator)微弱信号检测算法及其现场可编程门阵列(field programmable gate arrays,FPGA)实现技术.根据杜芬系统在混沌和大周期2种状态下相图的明显区别,运用基于相图分割的信号检测方法,在FPGA上实现了杜芬混沌算法与系统状态判别方法的结合.根据并行运算与流水线原理,对杜芬方程的结构进行调整.采用递推数列的方法计算正弦值,以便节约存储空间.使用VHDL硬件语言设计了杜芬阵子系统中核心的四阶龙格库塔(fourth order Runge Kutta algorithm,RK4)模块和状态检测模块,在vivado集成开发环境下仿真验证了设计的正确性.通过改变策动力的频率,系统可以检测各种频率的微弱正弦信号.经判断,该系统可实现对与系统信号同频率信号的检测.     

The climatic suitability for maize cultivation in China

To provide scientific support for planning maize production and designing countermeasures against the effects of climate change on the national maize crop, we analyzed the climatic suitability for cultivating maize across China. These analyses were based on annual climate indices at the Chinese national level; these indices influence the geographical distribution of maize cultivation. The annual climate indices, together with geographical information on the current cultivation sites of maize, the maximum entropy (MaxEnt) model, and the ArcGIS spatial analysis technique were used to analyze and predict maize distribution. The results show that the MaxEnt model can be used to study the climatic suitability for maize cultivation. The eight key climatic factors affecting maize cultivation areas were the frost-free period, annual average temperature, ≥0°C accumulated temperature, ≥10°C accumulated temperature continuous days, ≥10°C accumulated temperature, annual precipitation, warmest month average temperature, and humidity index. We classified climatic zones in terms of their suitability for maize cultivation, based on the existence probability determined using the MaxEnt model. Furthermore, climatic thresholds for a potential maize cultivation zone were determined based on the relationship between the dominant climatic factors and the potential maize cultivation area. The results indicated that the importance and thresholds of main climate controls differ for different maize species and maturities, and their specific climatic suitability should be studied further to identify the best cultivation zones. The MaxEnt model is a useful tool to study climatic suitability for maize cultivation.     

基于变步长随机共振的弱信号检测技术

针对绝热近似小参数随机共振难以满足工程实践中大参数下的弱信号检测，以及单一频率的共振分析在实际应用中的局限性问题，提出了一种变步长随机共振数值算法．该方法通过调整计算步长，使随机共振理论同时适用于犬、小参数条件下的弱信号特征提取．计算机仿真结果表明，对变步长随机共振后的信号作幅值谱和小波分析，均能准确得到低信噪比信号中的多个有用成分，充分证明该算法在大参数条件下可对弱信号中的多个特征频率产生共振输出．同时，变步长随机共振也可以有效抑制信号小波分解中由强噪声引起的边频干扰，提高小波分析在低信噪比信号检测中的可靠性．     

Plant litter decomposition in a semi-arid ecosystem controlled by photodegradation

The carbon balance in terrestrial ecosystems is determined by the difference between inputs from primary production and the return of carbon to the atmosphere through decomposition of organic matter. Our understanding of the factors that control carbon turnover in water-limited ecosystems is limited, however, as studies of litter decomposition have shown contradictory results and only a modest correlation with precipitation. Here we evaluate the influence of solar radiation, soil biotic activity and soil resource availability on litter decomposition in the semi-arid Patagonian steppe using the results of manipulative experiments carried out under ambient conditions of rainfall and temperature. We show that intercepted solar radiation was the only factor that had a significant effect on the decomposition of organic matter, with attenuation of ultraviolet-B and total radiation causing a 33 and 60 per cent reduction in decomposition, respectively. We conclude that photodegradation is a dominant control on above-ground litter decomposition in this semi-arid ecosystem. Losses through photochemical mineralization may represent a short-circuit in the carbon cycle, with a substantial fraction of carbon fixed in plant biomass being lost directly to the atmosphere without cycling through soil organic matter pools. Furthermore, future changes in radiation interception due to decreased cloudiness, increased stratospheric ozone depletion, or reduced vegetative cover may have a more significant effect on the carbon balance in these water-limited ecosystems than changes in temperature or precipitation.     

GNSS-R接收机信号捕获算法设计

在GNSS—R接收机的信号处理过程中,由于卫星和接收机之间的相对运动会产生较大的多普勒频移,同时大多数情况下接收机只能接收到比较弱的信号。而针对信号的这些特点,提出了一种对信号进行捕获的设计方法。用快速傅立叶变换(FFT)捕获算法将接收信号和本地再生伪码在时域的相关计算转换成频域的相乘计算,从而大大减少捕获时间,并用非相干积累的方法提高系统对于信号的捕获能力。同时,在这些计算完成之后,通过使用搜索检测器来保证在捕获概率变化较小的情况下,降低总的虚警概率。