Satellite measurements of the moon's magnetic field: A preliminary report

A preliminary analysis of the data from the UCLA magnetometer on board the Apollo 15 subsatellite indicates that remnant magnetization is a characteristic property of the Moon, that its distribution is such as to produce a rather complex pattern or fine structure, and that a detailed mapping of its distribution is feasible with the present experiment. The analysis also shows that lunar induction fields produced by transients in the interplanetary magnetic field are detectable at the satellite orbit so that in principle the magnetometer data can be used to determine the latitudinal and longitudinal as well as radial dependences of the distribution of electrical conductivity within the Moon. Finally, the analysis indicates that the plasma void or diamagnetic cavity which forms behind the Moon when the Moon is in the solar wind, is detectable at the satellite's orbit and that the flow of the solar wind near the limbs is usually rather strongly disturbed.Publication No. 981. Institute of Geophysics and Planetary Physics.     

Noble gases in ten Nullarbor chondrites: Exposure ages,terrestrial ages,and weathering effects

Abstract— We present concentration and isotopic composition of He, Ne, and Ar in ten chondrites from the Nullarbor region in Western Australia as well as the concentrations of ⁸⁴Ke, ¹²⁹Xe, and ¹³²Xe. From the measured cosmogenic ¹⁴C concentrations (Jull et al. 1995), shielding‐corrected production rates of ¹⁴C are deduced using cosmogenic ²²Ne/²¹Ne ratios. For shielding conditions characterized by ²²Ne/²¹Ne >1.10, this correction becomes significant and results in shorter terrestrial ages. The exposure ages of the ten Nullarbor chondrites are in the range of values usually observed in ordinary chondrites. Some of the meteorites have lost radiogenic gases as well as cosmogenic ³He. Most of the analyzed specimens show additional trapped Ar, Kr, and Xe of terrestrial origin. The incorporation of these gases into weathering products is common in chondrites from hot deserts.     

The Einstein static model of the universe as a whole

The Einstein static model of the universe as a whole is considered in Euclidean space and absolute time of a privileged reference frame. The universe as a whole is stable that specifies observers at rest relative to the global space of the universe. An observer in the centre of the universe is assumed to experience downward inertial acceleration along a certain radius due to the kinetic energy of the universe, with the total acceleration over all radii being equal zero. This yields the Doppler effect for the photon coming from the distant source that may explain the Hubble law in the static universe. The predictions of the model are qualitatively in agreement with the observations in the cosmological tests of a standard candle and a standard rod. Explanation of stretching of the light curve of SN Ia is proposed within the model considered.     

一种精确估计区域北斗接收机硬件延迟的方法

提出了一种精确估计区域北斗接收机硬件延迟(DCB)的方法。该方法不需要传统复杂的电离层模型,在已知一个参考站接收机硬件延迟的条件下,利用正常情况下电离层延迟量和卫星-接收机几何距离强相关这一特点,采用站间单差法来精确估计区域内BDS接收机的硬件延迟。试验结果表明,该方法单站估计的单站北斗接收机连续30d的硬件延迟RMS在0.3ns左右。通过GEO卫星双频观测值扣除已知卫星DCB和本文方法估计的接收机DCB,计算对应穿刺点一天的VTEC并和GIM格网内插结果并进行比对分析,二者大小和变化趋势均符合较好,进一步验证了本文提出的方法具有可靠性。     

Non-linear motions of Australian geodetic stations induced by non-tidal ocean loading and the passage of tropical cyclones

We investigate daily and sub-daily non-tidal oceanic and atmospheric loading (NTOAL) in the Australian region and put an upper bound on potential site motion examining the effects of tropical cyclone Yasi that crossed the Australian coast in January/February 2011. The dynamic nature of the ocean is important, particularly for northern Australia where the long-term scatter due to daily and sub-daily oceanic changes increases by 20–55 % compared to that estimated using the inverted barometer (IB) assumption. Correcting the daily Global Positioning System (GPS) time series for NTOAL employing either a dynamic ocean model or the IB assumption leads to a reduction of up to 52 % in the weighted scatter of daily coordinate estimates. Differences between the approaches are obscured by seasonal variations in the GPS precision along the northern coast. Two compensating signals during the cyclone require modelling at high spatial and temporal resolution: uplift induced by the atmospheric depression, and subsidence induced by storm surge. The latter dominates ( \(>\) 135 %) the combined net effect that reaches a maximum of 14 mm, and 10 mm near the closest GPS site TOW2. Here, 96 % of the displacement is reached within 15 h due to the rapid transit of cyclones and the quasi-linear nature of the coastline. Consequently, estimating sub-daily NTOAL is necessary to properly account for such a signal that can be 3.5 times larger than its daily-averaged value. We were unable to detect the deformation signal in 2-hourly GPS processing and show that seasonal noise in the Austral summer dominates and precludes GPS detection of the cyclone-related subsidence.     

Neutron Stars with a Quark Core. II. Basic Integral and Structural Parameters

A broad sample of computed realistic equations of state of superdense matter with a quark phase transition is used to construct a series of models of neutron stars with a strange quark core. The integral characteristics of the stellar configurations are obtained: gravitational mass, rest mass, radius, relativistic moment of inertia, and red shift from the star's surface, as well as the mass and radius of the quark core within the allowable range of values for the central pressure. The parameters of some of the characteristic configurations of the calculated series are also given and these are studied in detail. It is found that a new additional region of stability for neutron stars with strange quark cores may exist for some models of the equation of state.     

Hyperspectral remote sensing of evaporate minerals and associated sediments in Lake Magadi area, Kenya

Pleistocene to present evaporitic lacustrine sediments in Lake Magadi, East African Rift Valley, Kenya were studied and mapped using spectral remote sensing methods. This approach incorporated surface mineral mapping using space-borne hyperspectral Hyperion imagery together with laboratory analysis, including visible, near-infrared diffuse reflectance spectroscopy (VNIR) measurements and X-ray diffraction for selected rock and soil samples of the study area. The spectral signatures of Magadiite and Kenyaite, which have not been previously reported, were established and the spectral signatures of trona, chert series, volcanic tuff and the High Magadi bed were also analyzed.Image processing techniques, MNF (Minimum Noise Fraction) and MTMF (Mixture Tuned Matched Filtering) using a stratified approach (image analysis with and without the lake area), were used to enhance the mapping of evaporates. High Magadi beds, chert series and volcanic tuff were identified from the Hyperion image with an overall mapping accuracy of 84.3%. Even though, the spatial distribution of evaporites and sediments in Lake Magadi area change in response to climate variations, the mineralogy of this area has not been mapped recently. The results of this study shows the usefulness of the hypersspectral remote sensing to map the surface geology of this kind of environment and to locate promising sites for industrial open-pit trona mining in a qualitative and quantitative manner.     

Mapping transit‐based access: integrating GIS,routes and schedules

Seabed sediment textural parameters such as mud, sand and gravel content can be useful surrogates for predicting patterns of benthic biodiversity. Multibeam sonar mapping can provide near-complete spatial coverage of high-resolution bathymetry and backscatter data that are useful in predicting sediment parameters. Multibeam acoustic data collected across a ～1000 km² area of the Carnarvon Shelf, Western Australia, were used in a predictive modelling approach to map eight seabed sediment parameters. Four machine learning models were used for the predictive modelling: boosted decision tree, random forest decision tree, support vector machine and generalised regression neural network. The results indicate overall satisfactory statistical performance, especially for %Mud, %Sand, Sorting, Skewness and Mean Grain Size. The study also demonstrates that predictive modelling using the combination of machine learning models has provided the ability to generate prediction uncertainty maps. However, the single models were shown to have overall better prediction performance than the combined models. Another important finding was that choosing an appropriate set of explanatory variables, through a manual feature selection process, was a critical step for optimising model performance. In addition, machine learning models were able to identify important explanatory variables, which are useful in identifying underlying environmental processes and checking predictions against the existing knowledge of the study area. The sediment prediction maps obtained in this study provide reliable coverage of key physical variables that will be incorporated into the analysis of covariance of physical and biological data for this area.