Broad search for unstable resonant orbits in the planar circular restricted three-body problem

Unstable resonant orbits in the circular restricted three-body problem have increasingly been used for trajectory design using optimization and invariant manifold techniques. In this study, several methods for computing these unstable resonant orbits are explored including grid searches, flyby maps, and continuation. Families of orbits are computed focusing on orbits with multiple loops near the secondary in the Jupiter–Europa system, and their characteristics are explored. Different parameters such as period and stability are examined for each set of resonant orbits, and the continuation of several specific orbits is explored in more detail.     

Non-Linear Theory and Power-Law Models for Information Integration and Mineral Resources Quantitative Assessments

Singular physical or chemical processes may result in anomalous amounts of energy release or mass accumulation that, generally, are confined to narrow intervals in space or time. Singularity is a property of different types of non-linear natural processes including cloud formation, rainfall, hurricanes, flooding, landslides, earthquakes, wildfires, and mineralization. The end products of these non-linear processes can be modeled as fractals or multifractals. Hydrothermal processes in the Earth’s crust can result in ore deposits characterized by high concentrations of metals with fractal or multifractal properties. Here we show that the non-linear properties of the end products of singular mineralization processes can be applied for prediction of undiscovered mineral deposits and for quantitative mineral resource assessment, whether for mineral exploration or for regional, national and global planning for mineral resource utilization. In addition to the general theory and framework for the non-linear mineral resources assessment, this paper focuses on several power-law models proposed for characterizing non-linear properties of mineralization and for geoinformation extraction and integration. The theories, methods, and computer system discussed in this paper were validated using a case study dealing with hydrothermal Au mineral potential in southern Nova Scotia, Canada.     

Errors and correction of precipitation measurements in China

In order to discover the range of various errors in Chinese precipitation measurements and seek a correction method, 30 precipitation evaluation stations were set up countrywide before 1993. All the stations are reference stations in China. To seek a correction method for wind-induced error, a precipitation correction instrument called the ＂horizontal precipitation gauge＂ was devised beforehand. Field intercomparison observations regarding 29,000 precipitation events have been conducted using one pit gauge, two elevated operational gauges and one horizontal gauge at the above 30 stations. The range of precipitation measurement errors in China is obtained by analysis of intercomparison measurement results. The distribution of random errors and systematic errors in precipitation measurements are studied in this paper. A correction method, especially for wind-induced errors, is developed. The results prove that a correlation of power function exists between the precipitation amount caught by the horizontal gauge and the absolute difference of observations implemented by the operational gauge and pit gauge. The correlation coefficient is 0.99. For operational observations, precipitation correction can be carried out only by parallel observation with a horizontal precipitation gauge. The precipitation accuracy after correction approaches that of the pit gauge. The correction method developed is simple and feasible.     

Surface and groundwater quality characterization of Deoria District,Ganga Plain,India

A water quality investigation was carried out in the Deoria district, Ganga plain, to assess the suitability of surface and groundwaters for domestic, agricultural, and industrial purposes. As much as 50 representative samples from river and groundwater were collected from various stations to monitor the water chemistry of various ions, comprising Ca²⁺, Mg²⁺, Na⁺, K⁺, HCO₃ ⁻, SO₄ ²⁻, NO₃ ⁻, Cl⁻, F⁻, and trace metals, such as Fe, Cu, Mn, Zn, Cd, and Pb. The results showed that electrical conductance (EC), total dissolved solids (TDS), HCO₃ ⁻, Mg²⁺, Na⁺, and total hardness (TH) are above the maximum desirable limit, and apart from Fe and Mn all other trace metals are within the maximum permissible limit for drinking water. The calculated values for sodium absorption ratio (SAR), salinity, residual sodium carbonate (RSC), and permeability index (PI) indicate well to permissible use of water for irrigation. High values of Na%, RSC, and Mg-hazard (MH) at some stations restrict its use for agricultural purpose. Anthropogenic activities affect the spatial variation of water quality. Economic and social developments of the study area is closely associated with the characteristics of the hydrological network.     

Assessment of rock slope stability by probabilistic-based Slope Stability Probability Classification method along highway cut slopes in Adilcevaz-Bitlis (Turkey)

Rock slope stability is of great concern along highway routes as stability problems on cut slopes may cause fatal events as well as loss of property. In rock slope engineering, stability evaluations are commonly performed by means of analytical or numerical analyses, principally considering the factor of safety concept. As a matter of fact, the probabilistic assessment of slope stability is progressively getting popularity due to difficulties in assigning the most appropriate values to design parameters in analytical or numerical methods. Additionally, the effect of heterogeneities in rock masses and discontinuities on the analysis results is minimized through the probabilistic concept. In this study, slope stability of high and steep sedimentary rock cut slopes along a state highway in Adilcevaz-Bitlis (Turkey) was evaluated on the basis of probabilistic approach using the Slope Stability Probability Classification (SSPC) system. The probabilistic assessment indicates major slope stability problems because of discontinuity controlled and discontinuity orientation independent mass movements. Almost all studied cut slopes suffer from orientation-independent stability problems with very low stability probabilities. Additionally, the probability of planar and toppling failures is significantly high with respect to the SSPC system. The stability problems along the investigated rock slopes were also verified by field reconnaissance. Remedial measures such as slope re-design and reinforcement at the studied locations should be taken to prevent hazardous events along the highway. On the other hand, the probabilistic approach may be a useful tool during rock slope engineering to overcome numerous uncertainties when probabilistic and analytic results are compared.     

青藏高原净生态系统碳交换量的遥感评估模型研究

青藏高原作为世界海拔最高的区域,是全球气候变化的敏感区之一。定量估算这一区域的净生态系统碳交换量（NEE）有利于理解陆地生态系统碳平衡对未来气候变化的响应。本文构建了一个模拟该地区NEE动态变化的净碳收支模型（NCBM）。该模型由来源于MODIS影像的增强型植被指数（EVI）、陆地表面水分指数（LSWI）以及来源于地面观测的空气温度和短波辐射共同驱动,并利用青藏高原地区的3种植被类型（包括高寒灌丛、高寒湿地和高寒草甸）的碳通量长期观测数据对模型进行了校准和验证。结果表明,在模型校准站点年,NCBM模型可以模拟NEE观测值81%的变化,均方根误差（RMSE）为0.03molC/m2/d,模型效率（EF）为0.81。在模型验证站点年,NCBM模型可以预测NEE观测值84%的变化,RMSE为0.03molC/m2/d,EF为0.81。在大多数情况下,NCBM模型可以清晰地模拟各植被类型的NEE季节和年际变化。此外,NCBM模型因为结构简单,模型驱动变量易于获取等优势,具有在区域尺度上模拟NEE时空变化的潜力。但是该模型还需要进一步的改进和发展,特别需要提高对植被非常稀疏地区NEE变化的模拟能力。     

地震灾害风险评估及减灾策略研究——以贵州罗甸县为例

为探究贵州省地震灾害风险薄弱环节,减轻地震灾害风险,以贵州省罗甸县为示范,采用地震危险性概率分析方法对各乡镇进行危险性分析,开展地震灾害承灾体现场抽样调查,通过层次分析法和问卷调查的方式,首次构建乡镇级别的地震灾害风险和减灾能力指标体系,评估各乡镇地震灾害综合指数和程度,计算各乡镇地震灾害风险指数,确定红水河镇为高风险区、罗悃镇为中风险区、木引等7个乡镇为低风险区,并从建筑物设防、地震地质灾害及水库地震等角度剖析罗甸县地震灾害特点,从农村危房改造、移民搬迁、地质灾害防护及交通等方面提出减小地震灾害风险的建议。     

Misconceptions about the Hubble recession law

Almost all astronomers now believe that the Hubble recession law was directly inferred from astronomical observations. It turns out that this common belief is completely false. Those models advocating the idea of an expanding universe are ill-founded on observational grounds. This means that the Hubble recession law is really a working hypothesis. One alternative to the Hubble recession law is the tired-light hypothesis originally proposed by Zwicky (Proc. Nat. Acad. Sci. 15:773, 1929). This hypothesis leads to a universe that is an eternal cosmos continually evolving without beginning or end. Such a universe exists in a dynamical state of virial equilibrium. Observational studies of the redshift-magnitude relation for Type Ia supernovae in distant galaxies might provide the best observational test for a tired-light cosmology. The present study shows that the model Hubble diagram for a tired-light cosmology gives good agreement with the supernovae data for redshifts in the range 0<z<2. This observational test of a static cosmology shows that the real universe is not necessarily undergoing expansion nor acceleration. An erratum to this article can be found at     

A comparative study of sequential minimal optimization-based support vector machines,vote feature intervals,and logistic regression in landslide susceptibility assessment using GIS

Landslide susceptibility assessment using GIS has been done for part of Uttarakhand region of Himalaya (India) with the objective of comparing the predictive capability of three different machine learning methods, namely sequential minimal optimization-based support vector machines (SMOSVM), vote feature intervals (VFI), and logistic regression (LR) for spatial prediction of landslide occurrence. Out of these three methods, the SMOSVM and VFI are state-of-the-art methods for binary classification problems but have not been applied for landslide prediction, whereas the LR is known as a popular method for landslide susceptibility assessment. In the study, a total of 430 historical landslide polygons and 11 landslide affecting factors such as slope angle, slope aspect, elevation, curvature, lithology, soil, land cover, distance to roads, distance to rivers, distance to lineaments, and rainfall were selected for landslide analysis. For validation and comparison, statistical index-based methods and the receiver operating characteristic curve have been used. Analysis results show that all these models have good performance for landslide spatial prediction but the SMOSVM model has the highest predictive capability, followed by the VFI model, and the LR model, respectively. Thus, SMOSVM is a better model for landslide prediction and can be used for landslide susceptibility mapping of landslide-prone areas.