Incoherent radiation from relativistic electrons with power energetic spectrum

It is shown that an incoherent high-frequency radiation from an ensemble of relativistic particles with the power energy distribution is described by a certain general expression which covers practically all the cases of particle radiation in random electromagnetic fields of cosmic radiation sources.     

Effect of sampling and linkage on fault length and length–displacement relationship

The power-law exponent (n) in the equation: D=cL ⁿ , with D = maximum displacement and L = fault length, would be affected by deviations of fault trace length. (1) Assuming n=1, numerical simulations on the effect of sampling and linkage on fault length and length–displacement relationship are done in this paper. The results show that: (a) uniform relative deviations, which means all faults within a dataset have the same relative deviation, do not affect the value of n; (b) deviations of the fault length due to unresolved fault tip decrease the values of n and the deviations of n increase with the increasing length deviations; (c) fault linkage and observed dimensions either increase or decrease the value of n depending on the distribution of deviations within a dataset; (d) mixed deviations of the fault lengths are either negative or positive and cause the values of n to either decrease or increase; (e) a dataset combined from two or more datasets with different values of c and orders of magnitude also cause the values of n to deviate. (2) Data including 19 datasets and spanning more than eight orders of fault length magnitudes (10⁻²–10⁵ m) collected from the published literature indicate that the values of n range from 0.55 to 1.5, the average value being 1.0813, and the peak value of n _d (double regression) is 1.0–1.1. Based on above results from the simulations and published data, we propose that the relationship between the maximum displacement and fault length in a single tectonic environment with uniform mechanical properties is linear, and the value of n deviated from 1 is mainly caused by the sampling and linkage effects.     

THE MULTIPLICITY PRINCIPLE IN MODERN REMOTE SENSING METHODS AND ITS APPLICATION TO AGRICULTURAL IMAGE INTERPRETATION

The authors elaborate upon the “multiplicity principle” in remote sensing, i.e., the need for repeated imaging at a variety of scales, spatial resolutions, spectral bands, and times of imaging in order to attain the maximum information possible. They then explore the ways it can be applied in agricultural research, through two different image comparison and interpretation strategies. A detailed example is presented of the use of a multitemporal imaging strategy for the recognition of several agricultural crops from false color composite imagery. Translated by Edward Torrey, Alexandria, VA 22308 from: G. V. Dobrovol'skiy and V. L. Andronikov, eds., Aerokosmicheskiye metody v pochvo-vedenii i ikh ispol'zovaniye v sel'skom khozyaystve: sbornik nauchnykh trudov [Remote Sensing Methods in Soil Science and Their Utilization in Agriculture: A Collection of Scientific Works]. Moscow: Nauka, 1990, pp. 47-55.     

隧洞衬砌中湿喷钢纤维混凝土的应用

基于湿喷钢纤维混凝土的性质，讨论了喷射混凝土的特点及其在暂时支护与永久支护中的应用。     

北补连蛇绿岩的特征,形成环境及其构造意义

文中总结了北祁连蛇绿岩的特征，指出北祁连蛇绿岩大多具有ＭＯＲＢ的性质，有玻安岩产生，形成在弧后和岛弧环境，北祁连蛇绿岩大多侵位在岛弧增生楔或活动陆缘地体之上，蛇绿岩属于科迪勒拉型，早古生代的北祁连造山带属于科迪勒拉型造山带，部分蛇绿岩之上整合产出一套沉积一火山岩系，称为蛇绿岩的上覆岩系，指出蛇绿岩及其上覆岩系的枕状熔岩分别来自不同的源区，具有不同的构造意义，还讨论了北祁连早古生代板块构造格局，认为     

青藏高原及其邻近地区的地球物理场特征与大陆板块构造

本文搜集了现在已知的关于青藏高原地区的各种地球物理场特征,即:该区的地壳与上地幔构造,地磁场要素的分布,航空磁测的结果,古地磁极移轨迹,重力异常与均衡补偿,地热活动与温泉分布,地震活动以及深地震探测等研究结果,来探讨它与大陆板块构造的关系。 研究的初步结果表明,印度洋板块与欧亚板块交接地带的北界为雅鲁藏布江,南界为恒河平原的北缘。喜马拉雅地带为这两大板块碰撞与挤压的过渡带,其宽度约300公里左右。这一地带的大、小地震绝大部分是浅源地震,只在弧形山系和东西弧顶及其转折部位有中源地震。在这一过渡带内水热活动剧烈,重力也不均衡。 雅鲁藏布江以北到当雄一带,地壳厚度为70—73公里,喜马拉雅地区则为68—45公里左右,并向南翘起。地壳由多层介质组成,在下地壳中存在着低速层。断层面解表现为向南逆冲,主压应力轴基本上为南北向和北东向,且与震源深度相关。现在构造活动与地震活动似均逐渐向南移到主边界大断层一带。 在雅鲁藏布江以北,小震震源深度向南递加,而在恒河平原以北,则向北递加。此外,在上述两个地区均有零星的中源地震发生。因此,喜马拉雅地带的南北两侧有相向“俯冲”之势。在兴都库什地区,中源地震震源面北倾;在帕米尔地带,中源地震震源面南倾。因此,震源面构成了“V”字     

Atmospheric temperature sounding with the Fourier spectrometer

Preliminary results of a space experiment using the IKFS-2 infrared sounder (Meteor-M2 satellite) showed high-quality of measurements of spectra of the outgoing thermal radiation of the atmosphere–surface system and the adequacy of developed IR radiation atmospheric models in the 15-μm carbon gas absorption band used to recover the vertical profiles of the atmospheric temperature. Outgoing radiation spectra measured by IKFS-2 instruments make it possible to restore vertical temperature profiles with errors close to 1K in most of the 0–30 km high-altitude region, except for the lower troposphere and altitudes above 30 km, where these errors are close to 2–3K.     

Use of Machine Learning Methods to Reduce Predictive Error of Groundwater Models

Quantitative analyses of groundwater flow and transport typically rely on a physically‐based model, which is inherently subject to error. Errors in model structure, parameter and data lead to both random and systematic error even in the output of a calibrated model. We develop complementary data‐driven models (DDMs) to reduce the predictive error of physically‐based groundwater models. Two machine learning techniques, the instance‐based weighting and support vector regression, are used to build the DDMs. This approach is illustrated using two real‐world case studies of the Republican River Compact Administration model and the Spokane Valley‐Rathdrum Prairie model. The two groundwater models have different hydrogeologic settings, parameterization, and calibration methods. In the first case study, cluster analysis is introduced for data preprocessing to make the DDMs more robust and computationally efficient. The DDMs reduce the root‐mean‐square error (RMSE) of the temporal, spatial, and spatiotemporal prediction of piezometric head of the groundwater model by 82%, 60%, and 48%, respectively. In the second case study, the DDMs reduce the RMSE of the temporal prediction of piezometric head of the groundwater model by 77%. It is further demonstrated that the effectiveness of the DDMs depends on the existence and extent of the structure in the error of the physically‐based model.