A 12,000 Year Record of Explosive Volcanism in the Siple Dome Ice Core, West Antarctica

Air mass trajectories in the Southern Hemisphere provide a mechanism for transport to and deposition of volcanic products on the Antarctic ice sheet from local volcanoes and from tropical and subtropical volcanic centers. This study extends the detailed record of Antarctic, South American, and equatorial volcanism over the last 12,000 years using continuous glaciochemical series developed from the Siple Dome A (SDMA) ice core, West Antarctica. The largest volcanic sulfate spike ( 280 mu g/L) occurs at 5881 B. C. E. Other large signals with unknown sources are observed around 325 B. C. E. ( 270 mu g/L) and 2818 B. C. E. ( 191 mu g/L). Ages of several large equatorial or Southern Hemisphere volcanic eruptions are synchronous with many sulfate peaks detected in the SDMA volcanic ice chemistry record. The microprobe fingerprinting\u27\u27 of glass shards in the SDMA core points to the following Antarctic volcanic centers as sources of tephra found in the SDMA core: Balenny Island, Pleiades, Mount Berlin, Mount Takahe, and Mount Melbourne as well as Mount Hudson and possibly Mount Burney volcanoes of South America. Identified volcanic sources provide an insight into the poorly resolved transport history of volcanic products from source volcanoes to the West Antarctic ice sheet

A disposition of interpolation techniques

A large collection of interpolation techniques is available for application in environmental research. To help environmental scientists in choosing an appropriate technique a disposition is made, based on 1) applicability in space, time and space-time, 2) quantification of accuracy of interpolated values, 3) incorporation of ancillary information, and 4) incorporation of process knowledge. The described methods include inverse distance weighting, nearest neighbour methods, geostatistical interpolation methods, Kalman filter methods, Bayesian Maximum Entropy methods, etc. The applicability of methods in aggregation (upscaling) and disaggregation (downscaling) is discussed. Software for interpolation is described. The application of interpolation techniques is illustrated in two case studies: temporal interpolation of indicators for ecological water quality, and spatio-temporal interpolation and aggregation of pesticide concentrations in Dutch surface waters. A valuable next step will be to construct a decision tree or decision support system, that guides the environmental scientist to easy-to-use software implementations that are appropriate to solve their interpolation problem. Validation studies are needed to assess the quality of interpolated values, and the quality of information on uncertainty provided by the interpolation method

Application and improvement of soil spatial distribution mapping using advanced modelling techniques

The main purpose of this contribution is to develop  realistic prediction digital soil maps in order to increase their visuality, and to evaluate and compare the performance of different modeling techniques: a) Kriging, b) Artificial Neural Network – Multilayer Perceptron (ANN-MLP) and c) Multiple Polynomial Regressions (MPR). The following  criteria were used to determine selection of the testing site for the modeling: (1) intensive metal ore mining and metallurgical processing; (2) geomorphological natural features; (3) regular geological setting, and (4) the remaining minefields. The success of Digital Soil Mapping and the plausibility of prediction maps increases with the availability of spatial data, the availability of computing power for processing data, the development of data-mining tools, geographical information systems (GIS) and numerous applications beyond geostatistics. Advanced prediction modeling techniques, ANN-MLP and MPR include geospatial parameters sourced from Digital Elevation Models (DEM), land use and remote sensing, applied in combination with costly and time-consuming soil measurements, developed and finally incorporated into the models of spatial distribution in the form of 2D or 3D maps. Innovative approaches to modeling assist us in the reconstruction of different processes that impact the entire study area, simultaneously. This holistic approach represents a novelty in contamination mapping and develops prediction models to help in the reconstruction of main distribution pathways, to assess the real size of the affected area as well as improving the data interpretation.</p

Numerical Computation, Data Analysis and Software in Mathematics and Engineering

The present book contains 14 articles that were accepted for publication in the Special Issue “Numerical Computation, Data Analysis and Software in Mathematics and Engineering” of the MDPI journal Mathematics. The topics of these articles include the aspects of the meshless method, numerical simulation, mathematical models, deep learning and data analysis. Meshless methods, such as the improved element-free Galerkin method, the dimension-splitting, interpolating, moving, least-squares method, the dimension-splitting, generalized, interpolating, element-free Galerkin method and the improved interpolating, complex variable, element-free Galerkin method, are presented. Some complicated problems, such as tge cold roll-forming process, ceramsite compound insulation block, crack propagation and heavy-haul railway tunnel with defects, are numerically analyzed. Mathematical models, such as the lattice hydrodynamic model, extended car-following model and smart helmet-based PLS-BPNN error compensation model, are proposed. The use of the deep learning approach to predict the mechanical properties of single-network hydrogel is presented, and data analysis for land leasing is discussed. This book will be interesting and useful for those working in the meshless method, numerical simulation, mathematical model, deep learning and data analysis fields

Institutions, Inequality and Growth: A review of theory and evidence on the institutional determinants of growth and inequality

The difference in the development experiences between the most developed countries and the least developed countries of today is vast. Luxembourg’s per capita income is 200 times larger than Liberia’s. Even within the developing world, growth is very unequal. East Asia and parts of Latin America are growing at impressive rates, while many other countries - especially in Sub-Saharan Africa - struggle with sluggish and volatile growth. This study discusses the theoretical challenge posed in identifying the mechanisms that link institutions and equitable economic growth at various levels of aggregation. The relationship between governance modes and institutions on the one hand, and economic growth and development on the other hand, may take very different forms. This relates to the question of whether a single and unique combination of institutions and governance modes is optimal for (equitable) growth, or whether different governance modes and institutions may lead to good or equitable growth performance in different locations and historical contexts.development administration; growth policy; institutional framework;

The Globalization of Natural Resources: How External Actors Affect Political Survival in Resource Rich Countries

This dissertation examines the effect of external actors, including foreign investors, the home governments of foreign investors, and international organizations: IOs), on leadership survival in resource rich countries. According to the existing literature, resource rich countries care less about external reputation and have a higher level of political risks for foreign investors, so, theoretically, they would tend to nationalize the resource sectors, especially in the presence of resource nationalism. In reality, however, resource rich countries cooperate closely with foreign actors and join IOs that constrain themselves. This dissertation provides a theory to explain this puzzle, by modeling the interaction among foreign actors, the leaders of resource rich countries, and the domestic opposition. It argues that leaders of resource rich countries tend to maintain a close friendship with powerful foreign countries, not only because resource rich countries have strategic or economic importance, but also because they by nature face a higher level of revolutionary threat. By providing support to leaders who are friends of theirs, which depresses the opposition, foreign actors help the leaders of resource rich countries to stay in power. An empirical analysis on oil ownership and leadership turnover shows that a leader is more likely to survive when the oil is foreign owned. There are several foreign policy tools that foreign actors can use to assist the leaders, including military intervention, foreign aid, and support from IOs. Membership in IOs also has a similar effect on leadership survival, because IOs can legitimize the leaders and cover their unpopular activities

The NANOGrav 15-year Data Set: Evidence for a Gravitational-Wave Background

We report multiple lines of evidence for a stochastic signal that is correlated among 67 pulsars from the 15-year pulsar-timing data set collected by the North American Nanohertz Observatory for Gravitational Waves. The correlations follow the Hellings-Downs pattern expected for a stochastic gravitational-wave background. The presence of such a gravitational-wave background with a power-law-spectrum is favored over a model with only independent pulsar noises with a Bayes factor in excess of $10^{14}$, and this same model is favored over an uncorrelated common power-law-spectrum model with Bayes factors of 200-1000, depending on spectral modeling choices. We have built a statistical background distribution for these latter Bayes factors using a method that removes inter-pulsar correlations from our data set, finding $p = 10^{-3}$ (approx. $3\sigma$) for the observed Bayes factors in the null no-correlation scenario. A frequentist test statistic built directly as a weighted sum of inter-pulsar correlations yields $p = 5 \times 10^{-5} - 1.9 \times 10^{-4}$ (approx. $3.5 - 4\sigma$). Assuming a fiducial $f^{-2/3}$ characteristic-strain spectrum, as appropriate for an ensemble of binary supermassive black-hole inspirals, the strain amplitude is $2.4^{+0.7}_{-0.6} \times 10^{-15}$ (median + 90% credible interval) at a reference frequency of 1/(1 yr). The inferred gravitational-wave background amplitude and spectrum are consistent with astrophysical expectations for a signal from a population of supermassive black-hole binaries, although more exotic cosmological and astrophysical sources cannot be excluded. The observation of Hellings-Downs correlations points to the gravitational-wave origin of this signal.Comment: 30 pages, 18 figures. Published in Astrophysical Journal Letters as part of Focus on NANOGrav's 15-year Data Set and the Gravitational Wave Background. For questions or comments, please email [email protected]