Using radon-222 to study coastal groundwater/surface-water interaction in the Crau coastal aquifer (southeastern France)

Radon has been used to determine groundwater velocity and groundwater discharge into wetlands at the southern downstream boundary of the Crau aquifer, southeastern France. This aquifer constitutes an important high-quality freshwater resource exploited for agriculture, industry and human consumption. An increase in salinity occurs close to the sea, highlighting the need to investigate the water balance and groundwater behavior. Darcy velocity was estimated using radon activities in well waters according to the Hamada “single-well method” (involving comparison with radon in groundwater in the aquifer itself). Measurements done at three depths (7, 15 and 21 m) provided velocity ranging from a few mm/day to more than 20 cm/day, with highest velocities observed at the 15-m depth. Resulting hydraulic conductivities agree with the known geology. Waters showing high radon activity and high salinity were found near the presumed shoreline at 3,000 years BP, highlighting the presence of ancient saltwater. Radon activity has also been measured in canals, rivers and ponds, to trace groundwater discharges and evaluate water balance. A model of the radon spatial evolution explains the observed radon activities. Groundwater discharge to surface water is low in pond waters (4 % of total inputs) but significant in canals (55 l/m²/day).     

Predicting rock size distribution in mine blasting using various novel soft computing models based on meta-heuristics and machine learning algorithms

Blasting is well-known as an effective method for fragmenting or moving rock in open-pit mines. To evaluate the quality of blasting, the size of rock distribution is used as a critical criterion in blasting operations. A high percentage of oversized rocks generated by blasting operations can lead to economic and environmental damage. Therefore, this study proposed four novel intelligent models to predict the size of rock distribution in mine blasting in order to optimize blasting parameters, as well as the efficiency of blasting operation in open mines. Accordingly, a nature-inspired algorithm (i.e., firefly algorithm – FFA) and different machine learning algorithms (i.e., gradient boosting machine (GBM), support vector machine (SVM), Gaussian process (GP), and artificial neural network (ANN)) were combined for this aim, abbreviated as FFA-GBM, FFA-SVM, FFA-GP, and FFA-ANN, respectively. Subsequently, predicted results from the abovementioned models were compared with each other using three statistical indicators (e.g., mean absolute error, root-mean-squared error, and correlation coefficient) and color intensity method. For developing and simulating the size of rock in blasting operations, 136 blasting events with their images were collected and analyzed by the Split-Desktop software. In which, 111 events were randomly selected for the development and optimization of the models. Subsequently, the remaining 25 blasting events were applied to confirm the accuracy of the proposed models. Herein, blast design parameters were regarded as input variables to predict the size of rock in blasting operations. Finally, the obtained results revealed that the FFA is a robust optimization algorithm for estimating rock fragmentation in bench blasting. Among the models developed in this study, FFA-GBM provided the highest accuracy in predicting the size of fragmented rocks. The other techniques (i.e., FFA-SVM, FFA-GP, and FFA-ANN) yielded lower computational stability and efficiency. Hence, the FFA-GBM model can be used as a powerful and precise soft computing tool that can be applied to practical engineering cases aiming to improve the quality of blasting and rock fragmentation.     

ALMA observations of the circumstellar envelope around EP Aqr

Atacama Large Millimetre/sub-millimetre Array(ALMA) observations of CO(1–0) and CO(2–1) emissions from the circumstellar envelope of the asymptotic giant branch(AGB) star EP Aqr have been made with four times better spatial resolution than previously available. They are analysed with emphasis on the de-projection in space of the effective emissivity and flux of matter using as input a prescribed configuration of the velocity field, assumed to be radial. The data are found to display an intrinsic axisymmetry with respect to an axis making a small angle with respect to the line of sight. A broad range of wind configurations, from prolate(bipolar) to oblate(equatorial) has been studied and found to be accompanied by significant equatorial emission. Qualitatively, the effective emissivity is enhanced near the equator to produce the central narrow component observed in the Doppler velocity spectra and its dependence on star latitude generally follows that of the wind velocity with the exception of an omni-present depression near the poles. In particular, large equatorial expansion velocities produce a flared disc or a ring of effective emissivity and mass loss. The effect on the determination of the orientation of the star axis of radial velocity gradients, and possibly competing rotation and expansion in the equatorial disc, is discussed. In general,the flux of matter is found to reach a broad maximum at distances of the order of 500 AU from the star.Arguments are given that may be used to favour one wind velocity distribution over another. As a result of the improved quality of the data, a deeper understanding of the constraints imposed on morphology and kinematics has been obtained.     

The smallest of the largest: a new look at possible dwarfing in sauropod dinosaurs

Franz Baron Nopcsa recognised that the Late Cretaceous titanosaurid sauropod from Transylvania, Magyarosaurus dacus, was much smaller than the better known sauropods from the Upper Jurassic of the United States and even from Late Cretaceous deposits elsewhere in the world. In keeping with his biogeographic interpretations, Nopcsa viewed this difference as a consequence of body-size effects via island habitation. We present a preliminary re-evaluation of Nopcsa's claims and their heterochronic consequences using two approaches, viz. (1) regression analysis of humeral data as a means of establishing patterns in body size among titanosaurids, and (2) optimisation of humeral data onto titanosaurid cladograms to evaluate evolutionary trends within the clade. Our regression analysis is based on twenty species distributed among fourteen genera of neosauropods and uses length and mid-shaft mediolateral width of the humerus of presumed fully adult forms, and of growth samples that consist of postnatal to adult individuals. Linear regression analysis suggests that, among adult neosauropods, M. dacus appears to be represented by the smallest individuals; that M. dacus humeri appear to be more similar to those of subadults than to adults of other taxa; and that this juvenile morphology may constitute dwarfing in M. dacus by paedomorphosis. In order for these regressions to reflect their evolutionary context more fully, we also present optimisation analyses of humeral form within Titanosauroidea. Although many aspects of the phylogeny of this clade are relatively poorly resolved, preliminary results of our analyses are consistent with the conclusion that M. dacus was a heterochronic dwarf.     

‘White cranes fly over black cranes’: The longue durée of rural–urban migration in Vietnam

The changing nature of rural–urban migration, in the context of transition economies of East and Southeast Asia, is usually interpreted as an outcome of structural transformation, while the longue durée of these migration flows tends to be neglected. Adopting a historical perspective, supported by the ’migration as resistance’ approach, this paper examines the changes in rural–urban migration dynamics in Vietnam from the 1950s to 2010 in relation to the country’s political and economic reforms (Ð?i M?i). Drawing on a case study of female migration between Phu Khe and Hanoi, it analyses how migrants resist and undermine state control over population mobility in order to pursue their movement and migration, and how they develop their migration networks over time. By doing so, the paper highlights a gradual process of the changing nature of rural–urban migration in which migrants themselves, through their resistance to governance of mobility and their establishment of migration networks prior to Ð?i M?i, play an important role.     

Evaluation of five gridded rainfall datasets in simulating streamflow in the upper Dong Nai river basin,Vietnam

Rainfall data with an appropriate spatial resolution is a key input to hydrological models. However, networks of rain gauges are often sparsely and unevenly distributed in large catchments, especially in developing countries. High-resolution rainfall datasets, such as the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), the Climate Forecast System Reanalysis (CFSR), the Climatic Research Unit Time Series (CRU-TS), the Global Precipitation Climatology Centre (GPCC) and the Tropical Rainfall Measuring Mission (TRMM), have become available to overcome such limitations. The objective of this study was to evaluate the impacts of four land-based rainfall products (APHRODITE, CFSR, CRU-TS, and GPCC) and a satellite-based rainfall product (TRMM) on streamflow of the upper catchment of Tri An reservoir in Vietnam using the Hydrological Modeling System (HEC-HMS). In addition, the available rain gauges data were used for comparison purpose. Result indicates that the TRMM and GPCC data show their best match to rain gauges data in simulating the streamflow in the period 1999–2007. Generally, the results indicate that the TRMM and GPCC data could be alternative solutions.     

Lab-scale performance of selected expandable clays under HLW repository conditions

Smectite clay has been proposed for embedding canisters with highly radioactive waste in deep repositories because of its isolating capacity. Montmorillonite-rich bentonite is a premier buffer candidate for many national organizations that are responsible for disposal of such waste. Experience from the use of drilling mud at large depths indicates that other smectite clay minerals are more stable chemically and saponite is one of them. The physical properties of smectitic mixed-layer minerals like Friedland clay are known to be less sensitive to high salt contents and such clay may also be a buffer candidate. Montmorillonite-rich MX-80 clay, Greek saponite with a minor amount of palygorskite, and Friedland clay were investigated in hydrothermal tests with dense samples confined in oedometers with 95 °C temperature at one end, which was made of copper, and 35 °C at the other, for 8 weeks. A 1 % CaCl₂ solution was circulated through a filter at the cold end. At the end of the tests, the samples were sliced into three parts, which were tested with respect to expandability, hydraulic conductivity, and chemical composition. The tests showed that while the saponite was hardly changed at all and did not take up any copper, MX-80 underwent substantial changes in physical performance and adsorbed significant amounts of copper. The Friedland clay sample was intermediate in both respects.     

Evaluation of deep learning algorithms for national scale landslide susceptibility mapping of Iran

The identification of landslide-prone areas is an essential step in landslide hazard assessment and mitigation of landslide-related losses.In this study,we applied two novel deep learning algorithms,the recurrent neural network(RNN)and convolutional neural network(CNN),for national-scale landslide susceptibility mapping of Iran.We prepared a dataset comprising 4069 historical landslide locations and 11 conditioning factors(altitude,slope degree,profile curvature,distance to river,aspect,plan curvature,distance to road,distance to fault,rainfall,geology and land-sue)to construct a geospatial database and divided the data into the training and the testing dataset.We then developed RNN and CNN algorithms to generate landslide susceptibility maps of Iran using the training dataset.We calculated the receiver operating characteristic(ROC)curve and used the area under the curve(AUC)for the quantitative evaluation of the landslide susceptibility maps using the testing dataset.Better performance in both the training and testing phases was provided by the RNN algorithm(AUC=0.88)than by the CNN algorithm(AUC=0.85).Finally,we calculated areas of susceptibility for each province and found that 6%and 14%of the land area of Iran is very highly and highly susceptible to future landslide events,respectively,with the highest susceptibility in Chaharmahal and Bakhtiari Province(33.8%).About 31%of cities of Iran are located in areas with high and very high landslide susceptibility.The results of the present study will be useful for the development of landslide hazard mitigation strategies.