Theoretical discussion and Monte-Carlo simulations for a Negative Binomial process paradox

The idea of an over-threshold sampling is to retain all the events of a time-series exceeding a given threshold. The probabilistic analysis implies estimating two statistical models, one describing the occurrence of the events (date of the events), the other describing their magnitude (value of the local maximum). These two models are then combined to obtain the distribution of the annual maxima. A well-known result of a Poisson process is that waiting time, defined as the duration between two successive events exceeding the threshold, is exponentially distributed. The assertion that the waiting time of a Negative Binomial process is also exponentially distributed seems to be in obvious contradiction with the Poisson process properties. A theoretical discussion and Monte-Carlo simulations are presented to solve this apparent paradox.     

Estimation of Organic Pesticide Residues in Wines of Moldova

This paper presents the study of pesticide residues in Moldovan wine products originating from traditional agriculture because the appreciation of these compounds is an important aspect of food safety. During 2007–2010, about 3000 analyses of wine samples using GC‐MS were investigated. Persistent organic pollutants (POPs), i.e., α‐, β‐, γ‐HCH, aldrine, and heptachlor were not found in any of the samples. Insignificant quantities of metalaxyl and mefenoxam were found in some wine samples. The missing of POPs in wine products represents an important quality feature. The study showed that if growers comply with rules of phytosanitary treatments and the waiting period is respected, the content of pesticide residues can be reduced to safe limits. Also, the list of approved pesticides must be regularly revised, taking into account the degree of toxicity. Additionally, growers are to be constantly informed about effectuated changes.     

华北地区强震的等待时间研究

从概率论出发,推导出从上一次地震发生时间到下一次地震发生时间(等待时间)的数学表达式,并给出了威布尔分布、指数分布、均匀分布的等待时间表达式。在此基础上,以河北省及其邻近地区为例,用3个分布函数分别计算了各地区发生5.0级以上地震的等待时间发震概率及回溯性检验,并利用AIC准则对何种分布函数更适合华北地区5.0级以上强震危险性分析进行了讨论。     

Analysis of Temporal Structures of Seismic Events on Different Scale Levels

A statistical model for describing the energy scaling of the distribution of inter-event times is described. By considering the diverse region seismicity (natural and induced) on different scale (energy/magnitude) levels the self-similarity of the distribution has been determined. A comparison between the distribution of inter-event times on different scale levels and the most popular distributions of reliability theory has been carried out. The distribution of inter-event times for different scale levels is well approximated by the Weibull distribution. The Weibull distribution, with parameters which obey the scaling model and the Gutenberg-Richter law, has been tested.     

On the Statistics of Wind Gusts

Wind measurementsnear the North Seaborder of Northern Germany andvelocity measurements under localisotropic conditions of a turbulent wakebehind a cylinder are compared. It is shownthat wind gusts, measured by means ofvelocity increments, do show similar statisticsto the laboratory data if they are conditionedon an averaged wind speed value.Clear differences between the laboratory dataand the atmospheric measurements arefound for the waiting time statistics betweensuccessive gusts above acertain threshold.     

云南泸西县云鹏水电站坝基基础工程处理

大坝基础帷幕灌浆工程中采用新技术、新工艺，使工程质量大幅提高，也使这些新技也能在实践中得到发展和完善，为工程良好的质量和效益打下了坚实的基础。     

Unified scaling theory for distributions of temporal and spatial characteristics in seismology

The paper describes the unified scaling theory for distribution functions of temporal and spatial characteristics in seismology. It is based on the scaling of seismological characteristics calculated for various energy–spatial–temporal intervals. The common mathematical methods for the scaling of distribution functions are developed. The means to test possibility of such scaling are found as well. The relationship between the unified scaling theory and other present scaling approaches is determined. The theory is applied to two characteristics of different seismoactive regions. The first characteristic is the waiting time between earthquakes ΔT, the second one is a new space parameter ΔD_min, which is the minimum distance of a current seismic event to the nearest (in space) neighbor in an energy–spatial–temporal interval. The distribution of the characteristics ΔT and ΔD_min allows estimating the time interval to the next earthquake and the distance of the following earthquake from previous earthquakes. Thus, these characteristics are very important for seismic hazard estimations. Scaling of distributions functions is proven to be successful for ΔD_min in all energy–spatial–temporal intervals and for ΔT with variations of energy/magnitude range. The distribution function of ΔT for various time domains was stable in only 60% of the cases, and near to unstable for spatial variations.     

Modelling fundamental waiting time distributions for earthquake sequences

The distribution of waiting times between time-neighbouring events for a time series obeying the Omori law is examined theoretically and numerically with the aim of understanding the characteristics of these distributions, how these characteristics change (e.g. scale) with the parameters of the Omori series, and thus how empirical waiting time data may be correctly interpreted. It is found that the waiting time distribution, for a single Omori aftershock sequence, consists in general of two power law segments followed by a rapid decay at larger waiting times. The analyses are illustrated using real data from the SIL network on Iceland. This data often shows characteristics predominantly consistent with the Omori law, but there are significant exceptions. We conclude that waiting time distributions and related statistical analysis has meaningful potential for the analysis of earthquake data sets, as a step towards developing physical models of the earthquake process.