The Gondwana Orogeny in northern North Patagonian Massif:Evidences from the Caita Có granite,La Se?a and Pangaré mylonites,Argentina

Structural analyses in the northern part of the North Patagonia Massif,in the foliated Caita Co granite and in La Sena and Pangare mylonites,indicate that the pluton was intruded as a sheet-like body into an opening pull-apart structure during the Gondwana Orogeny.Geochronological studies in the massif indicate a first,lower to middle Permian stage of regional deformation,related to movements during indentation tectonics,with emplacement of foliated granites in the western and central areas of the North Patagonian Massif.Between the upper Permian and lower Triassic,evidence indicates emplacement of undeformed granitic bodies in the central part of the North Patagonian Massif.A second pulse of deformation between the middle and upper Triassic is related to the emplacement of the Caita Co granite,the development of mylonitic belts,and the opening of the Los Menucos Basin.During this pulse of deformation,compression direction was from the eastern quadrant.     

Palaeoenvironmental Reconstruction of the Early to Middle Miocene Sequence in West Central Sinai,Egypt, as Revealed from Fossil Diatoms

A detailed analysis of the diatoms from the sedimentary sequence exposed in Abu Qada basin, west central Sinai, was used to determine the palaeoenvironmental changes during the Lower to Middle Miocene. A total of 85 diatom species and varieties belonging to 37 genera were identified from 154 samples collected throughout the stratigraphic succession. The lithological characters of the studied samples varied between sandstone, silty interbeds, sandy shales, shales, and terminated with anhydrite and limestones. These rock units are included in two lithostratigraphic formations (Rudies and Kareem), which are separated by a marked unconformity. The distribution and preservation of fossil diatoms in the sedimentary record are examined with the aim of outlining the temporal and spatial variation in the composition of the diatom assemblages, in order to estimate the changes in depositional environments during the Lower to Middle Miocene. The distributional pattern of the recorded diatom taxa distinguished four diatom eco-zones. The environment of each eco-zone is deduced and a proposed paleobathymetric change and depositional history of the Miocene sediments in the studied area are given.     

Is Ziarat a Potential Site for Conventional or Unconventional Energy Resources?

A structural interpretation of the Ziarat block in the Balochistan region (a part of the Suleiman Fold and Thrust Belt) has been carried out using seismic and seismological data. Seismic data consists of nine 2.5D pre‐stack migrated seismic lines, whereas the seismological data covers the Fault Plane Solution and source parameters. Structural interpretation describes two broad fault sets of fore and back thrusts in the study area that have resulted in the development of pop‐up structures, accountable for the structural traps and seismicity pattern in terms of seismic hazard. Seismic interpretation includes time and depth contour maps of the Dungan Formation and Ranikot group, while seismological interpretation includes Fault Plane Solution, that is correlated with a geological and structural map of the area for the interpretation of the nature of the subsurface faults. Principal stresses are also estimated for the Ranikot group and Dungan Formation. In order to calculate anisotropic elastic properties, the parameters of the rock strength of the formations are first determined from seismic data, along with the dominant stresses (vertical, minimum horizontal, and maximum horizontal). The differential ratio of the maximum and minimum horizontal stresses is obtained to indicate optimal zones for hydraulic fracturing, and to assess the potential for geothermal energy reservoir prospect generation. The stress maps indicate high values towards the deeper part of the horizon, and low towards the shallower part, attributed to the lithological and structural variation in the area. Outcomes of structural interpretation indicate a good correlation of structure and tectonics from both seismological and seismic methods.     

Intraseasonal oscillation of the southwest monsoon over Sri Lanka and evaluation of its subseasonal forecast skill

斯里兰卡的雨季发生于5-9月间,主要受西南季风的控制.本文发现该地区的西南季风降水存在很强的次季节变率,主导周期为10-35天.降水的季节内变化与西传的异常气旋有关.进一步,利用S2S比较计划中欧洲中心的数值预报模式(ECMWF)提供的回报试验数据,评估了当今动力模式对斯里兰卡西南季风次季节变化的预报技巧.结果显示,对季风指数的预测技巧超过30天,而对降水指数的预测技巧大约两周,且模式的预报技巧具有明显的年际差异.分析表明,能否正确模拟出大尺度环流对热带对流的响应是影响斯里兰卡降水预测的重要因子.     

基于非均质地层参数表征的颗粒流模型构建

非均质地层参数的获取与表征方法是浅层地质体改造的重要依据。基于非均质地层的地质建模,表征具有随机不确定性和模糊不确定性的土体表观参数和物理力学参数。利用 Weibull 分布统计描述局部地层信息,并应用Diamond-Square分形插值方法,结合差分盒子维计算非均质地层分形维数,进一步合理演算整体地层参数。采用PFC3D数值模拟软件,结合马尔科夫链蒙特卡洛方法采样数据,对非均质地层块石颗粒及土颗粒进行建模。通过非均质地层模拟结果,发现其破坏过程与应力应变曲线要比均质土体复杂得多,由于块石大颗粒的含量、分布特性对土样力学性质影响显著。本文建模方法有助于非均质地层参数表征研究。     

Geology and Mineral Chemistry of Uranium- and Thorium-bearing Minerals in Rare-Metal (NYF) Pegmatites of Um Solimate,South Eastern Desert,Egypt

The garnet muscovite granitic pegmatite of Um Solimate, in southern Egypt, represents a promising asset for strategic and economic metals, especially Bi–Ni–Ag–Nb–Ta as well as U and Th. The ore bodies occur as large masses, pockets and/or veins of very coarse-grained pegmatites, which consist mainly of K-feldspar, quartz and albite with subordinate muscovite, garnet, and biotite. Radiometric data revealed that eU- and eTh-contents of the pegmatites reach up to 39 ppm and 82 ppm, respectively. The studied pegmatites are enriched in primary U and Th minerals (uraninite, coffinite, thorianite and uranothorite) as well as Hf-rich zircon and monazite, which give rise to anomalous radioactive zones. Niobium-tantalium-bearing minerals (i.e. ferrocolumbite, microlite and uranopyrochlore), xenotime, barite, galena, fluorite, and apatite are ubiquitous, and, consequently, the studied pegmatites belong tothe Niobium–Yttrium–Fluorine-type (NYF) family. The noble metal mineralization includes argentite (Ag2S), native Ni and Bi as well as bismite and bismoclite. In addition, beryl and tourmaline are observed in pegmatites near the contact with metasediments and ultramafic bodies. The observed compositional variations of Ta/(Ta+Nb) and Mn/(Mn+Fe) ratios in columbite (0.08–0.45 and 0.11–0.57, respectively) and Hf contents in zircon (3.54–6.46 wt%) may reflectan extreme degree of magmatic fractionation leading to formation of the pegmatite orebody.     

Spatial landslide susceptibility assessment using machine learning techniques assisted by additional data created with generative adversarial networks

In recent years,landslide susceptibility mapping has substantially improved with advances in machine learning.However,there are still challenges remain in landslide mapping due to the availability of limited inventory data.In this paper,a novel method that improves the performance of machine learning techniques is presented.The proposed method creates synthetic inventory data using Generative Adversarial Networks(GANs)for improving the prediction of landslides.In this research,landslide inventory data of 156 landslide locations were identified in Cameron Highlands,Malaysia,taken from previous projects the authors worked on.Elevation,slope,aspect,plan curvature,profile curvature,total curvature,lithology,land use and land cover(LULC),distance to the road,distance to the river,stream power index(SPI),sediment transport index(STI),terrain roughness index(TRI),topographic wetness index(TWI)and vegetation density are geo-environmental factors considered in this study based on suggestions from previous works on Cameron Highlands.To show the capability of GANs in improving landslide prediction models,this study tests the proposed GAN model with benchmark models namely Artificial Neural Network(ANN),Support Vector Machine(SVM),Decision Trees(DT),Random Forest(RF)and Bagging ensemble models with ANN and SVM models.These models were validated using the area under the receiver operating characteristic curve(AUROC).The DT,RF,SVM,ANN and Bagging ensemble could achieve the AUROC values of(0.90,0.94,0.86,0.69 and 0.82)for the training;and the AUROC of(0.76,0.81,0.85,0.72 and 0.75)for the test,subsequently.When using additional samples,the same models achieved the AUROC values of(0.92,0.94,0.88,0.75 and 0.84)for the training and(0.78,0.82,0.82,0.78 and 0.80)for the test,respectively.Using the additional samples improved the test accuracy of all the models except SVM.As a result,in data-scarce environments,this research showed that utilizing GANs to generate supplementary samples is promising because it can improve the predictive capability of common landslide prediction models.     

Brittleness index predictions from Lower Barnett Shale well-log data applying an optimized data matching algorithm at various sampling densities

The capability of accurately predicting mineralogical brittleness index(BI)from basic suites of well logs is desir-able as it provides a useful indicator of the fracability of tight formations.Measuring mineralogical components in rocks is expensive and time consuming.However,the basic well log curves are not well correlated with BI so correlation-based,machine-learning methods are not able to derive highly accurate BI predictions using such data.A correlation-free,optimized data-matching algorithm is configured to predict BI on a supervised basis from well log and core data available from two published wells in the Lower Barnett Shale Formation(Texas).This transparent open box(TOB)algorithm matches data records by calculating the sum of squared errors be-tween their variables and selecting the best matches as those with the minimum squared errors.It then applies optimizers to adjust weights applied to individual variable errors to minimize the root mean square error(RMSE)between calculated and predicted(BI).The prediction accuracy achieved by TOB using just five well logs(Gr,pb,Ns,Rs,Dt)to predict BI is dependent on the density of data records sampled.At a sampling density of about one sample per 0.5 ft BI is predicted with RMSE～0.056 and R2～0.790.At a sampling density of about one sample per 0.1 ft BI is predicted with RMSE～0.008 and R2～0.995.Adding a stratigraphic height index as an additional(sixth)input variable method improves BI prediction accuracy to RMSE～0.003 and R2～0.999 for the two wells with only 1 record in 10,000 yielding a BI prediction error of＞±0.1.The model has the potential to be applied in an unsupervised basis to predict BI from basic well log data in surrounding wells lacking mineralogical measure-ments but with similar lithofacies and burial histories.The method could also be extended to predict elastic rock properties in and seismic attributes from wells and seismic data to improve the precision of brittleness index and fracability mapping spatially.     

New observations and transit solutions of the inflated exoplanets HAT-P-40b and HAT-P-51b

We present high-precision photometric observations of the transiting exoplanets HAT-P-40 b and HAT-P-51 b by the Rozhen 2-m telescope.The newly-observed transit of HAT-P-40 b is the first one with a complete curve.The orbital periods of the two targets were improved.We modeled the observed transits and found bigger stellar radii than those derived from the stellar models.The planet radii of HATP-40 b and HAT-P-51 b obtained from our transit solutions are bigger than the values calculated by the empirical relations for Jupiter-mass and Saturn-mass planets respectively.Their values reveal the highlyinflated nature of the two targets,especially that of HAT-P-51 b.We established that the best transit solutions correspond to a quadratic limb-darkening law.The fitted limb-darkening coefficients of HAT-P-40 are close to the theoretical ones while those of HAT-P-51 are a little different.The precise astrometric Gaia distances of the two targets are smaller by 6%–7%than the calculated values from the stellar models.We propose the Gaia distances to be used for improvement of the stellar models as well as for more reliable calculation of the parameters of the known exoplanets.     

气候影响下的荒漠下的荒漠化监测

根据揭示沙漠化扩张内在规律的相关气候驱动因子的假说,气候作用影响之下的沙漠化是在具反射率-降水正、负反馈特点的气候系统之中的区域干旱化过程与干旱土壤退化过程相互作用的结果。在辐射调节下的地表下垫面温度占主导的条件下,气候成因的沙漠化是由区域气候系统反馈所形成。正反馈的外部调节因子是降水量的变化和极端降水事件(特别是旱灾)的出现频率,降水量减少以及降水频率的降低直接影响沙漠化的程度。20世纪下半叶,人类因素导致的干旱土地退化作为另外的正反馈调节因子,其重要性正在增加。通常正反馈的扩大趋势会被通过蒸腾而进行的地表温度调节的负反馈所抑制。由正反馈到负反馈的转换是通过地球表面与大气层之间的热量交换的调节所确定的,其中非潜热因子处于增加状态。上述情况在反射率和地表温度同时增加的条件下发生。在超出绿色植物生物量及其NDVI指数阈值的条件下,负反馈向正反馈的转换就会发生。人为作用导致的植被退化加快了向绿色植物生物量阈值逼近的进程,从而引起气候因素驱动的沙漠化扩大。一个主要由气候因素影响的荒漠化区域,在大多数情况下,其绿色生物量均在季节变化和年际变化中达到了阈值。在中度的人为影响的植被退化条件下,这些地域一般都包括部分干旱与半干旱土地。然而有时,人类活动也会导致干旱的半湿润土地退化。本文运用Turan和Sahel地区1982-2001年NDVI指数的监测结果,分析了全球变暖和人为作用导致的土地退化。