Automatic Determination of Stellar Atmospheric Parameters Using Neural Networks and Instance-Based Machine Learning

In this article we show how machine learning methods can beeffectively applied to the problem of automatically predictingstellar atmospheric parameters from spectral information, a veryimportant problem in stellar astronomy. We apply feedforwardneural networks, Kohonen's self-organizing maps andlocally-weighted regression to predict the stellar atmosphericparameters effective temperature, surface gravity and metallicityfrom spectral indices. Our experimental results show that thethree methods are capable of predicting the parameters with verygood accuracy. Locally weighted regression gives slightly betterresults than the other methods using the original dataset asinput, while self-organizing maps outperform the other methods when significant amounts of noise are added. We also implemented a heterogeneous ensemble of predictors, combining the results given by the three algorithms. This ensemble yields better results than any of the three algorithms alone, using both the original and the noisy data.     

Prediction of Stellar Atmospheric Parameters using Instance-Based Machine Learning and Genetic Algorithms

In this article we present a method for the automated prediction of stellar atmospheric parameters from spectral indices. This method uses a genetic algorithm (GA) for the selection of relevant spectral indices and prototypical stars and predicts their properties, using the k-nearest neighbors method (KNN). We have applied the method to predict the effective temperature, surface gravity, metallicity, luminosity class and spectral class of stars from spectral indices. Our experimental results show that the feature selection performed by the genetic algorithm reduces the running time of KNN up to 92%, and the predictive accuracy error up to 35%. This revised version was published online in July 2006 with corrections to the Cover Date.     

Otolith shape as a stock discrimination tool for ling (Genypterus blacodes) in the fjords of Chilean Patagonia

ABSTRACT

Genypterus blacodes, in terms of its fishing history and local economic importance, is an emblematic species harvested in Chilean Patagonia (41°00’–57°00’S). Most of the current fisheries and biological knowledge of this species come from the open ocean, whereas information about the species in fjords and inner channels is fragmentary. In 2018, two research surveys targeting G. blacodes were conducted in the fjords and inner channels of Chilean Patagonia. A total of 253 pairs of sagittal otoliths were sampled at three different localities, and their contours were modelled using wavelet analysis as a tool for stock discrimination. Contours were compared using canonical analysis, and classification was performed using linear discriminant and Random Forest analyses. The results indicated that the wavelet method is efficient in modelling otolith contours, and the discriminant analyses showed differences among fishing grounds across the latitudinal gradient, thus confirming the hypothesis that G. blacodes conform to at least two separate stock units in Chilean Patagonia. Fishing grounds that were closer in space showed higher levels of misclassification. The discussion focuses on how environmental variables and the geography of fjords shape stock differences and how this information can be used for the sustainable management of G. blacodes.     

Effects of crab–halophytic plant interactions on creek growth in a S.W. Atlantic salt marsh: A Cellular Automata model

The Bahía Blanca Estuary (38° 50′ S, and 62° 30′ W) presents salt marshes where interactions between the local flora (Sarcocornia perennis) and fauna (Chasmagnathus granulatus) generate some kind of salt pans that alter the normal water circulation and condition its flow and course towards tidal creeks. The crab–vegetation dynamics in the salt marsh presents variations that cannot be quantified in a reasonable period of time. The interaction between S. perennis plant and C. granulatus crab is based on simple laws, but its result is a complex biological mechanism that causes an erosive process on the salt marsh and favors the formation of tidal creeks. To study it, a Cellular Automata model is proposed, based on the laws deduced from the observation of these phenomena in the field, and then verified with measurable data within macroscale time units. Therefore, the objective of this article is to model how the interaction between C. granulatus and S. perennis modifies the landscape of the salt marsh and influences the path of tidal creeks. The model copies the basic laws that rule the problem based on purely biological factors.The Cellular Automata model proved capable of reproducing the effects of the interaction between plants and crabs in the salt marsh. A study of the water drainage of the basins showed that this interaction does indeed modify the development of tidal creeks. Model dynamics would likewise follow different laws, which would provide a different formula for the probability of patch dilation. The patch shape can be obtained changing the pattern that dilates.     

Observation of gravity waves in a boreal forest

In this paper we report the results of the analysis of two 60-min wave events that occurred in a boreal aspen forest during the 1994 BOREAS (Boreal Ecosystems-Atmosphere Study) field experiment. High frequency wind and temperature data were provided by three 3-D sonic anemometer/thermometers and fourteen fine-wire thermocouples positioned within and above the forest. Wave phase speeds, estimated from information revealed by spectral analysis and linear plane wave equations, are 2.2 and 1.3 m s^-1 for the two events. The wavelengths are 130 m and 65 m respectively and are much larger than the vertical wave displacements. There is strong evidence from the present analysis and from the literature supporting our postulate that these waves are generated by shear instability. We propose that wind shear near the top of the stand is often large enough to reduce the gradient Richardson number below the critical value of 0.25 and thus is able to trigger the instability. When external conditions are favorable, the instability will grow into waves.     

Role of Wavelets in the Physical and Statistical Modelling of Complex Geological Processes

— Today, wavelets are recognized to have a wide range of useful properties that allow them to treat effectively multifacet problems, such as data compression, scale-localization analysis, feature extraction, statistics, numerical simulation, visualization, and communication. Second-generation wavelets represent a recent improvement of the wavelet algorithm, allowing for greater flexibility in the spatial domain and other computational advantages. We will show how these wavelets can be employed to extract large-scale coherent structures from (1) three-dimensional turbulent flows and (2) high Rayleigh number thermal convection. We will discuss the concept of modelling via decomposition into coherent and incoherent fields, taking into account the effect of the incoherent field via statistical modelling. We will discuss wavelet properties and how they can be utilized and integrated in handling large-scale problems in earthquake physics and other nonlinear phenomena in the geosciences.     

Response of suspended sediment particle size distributions to changes in water chemistry at an Andean mountain stream confluence receiving arsenic rich acid drainage

Acid drainage is an important water quality issue in Andean watersheds, affecting the sustainability of urban, agricultural, and industrial activities. Mixing zones receiving acid drainage are critical sites where changes in pH and chemical environment promote the formation and dissolution of iron and aluminum oxy/hydroxides. These particles can significantly change the speciation of toxic metals and metalloids throughout drainage networks via sorption, desorption, and settling processes. However, little is known about the behavior of particle size distributions (PSDs) in streams affected by acid drainage and their relationship to metal speciation. This work studied: (a) the PSDs for a wide range of mixing ratios found at a fluvial confluence affected by acid drainage, and (b) the response of PSDs and arsenic speciation to environmental changes found when the particles approach complete mixing conditions. The confluence between the Azufre River (pH ~ 2, high concentration of dissolved metals) and Caracarani River (pH = 8.6, low concentration of dissolved metals) was used as a representative model for study. Field measurements show a bimodal PSD with modal diameters of ~50 and 300 μm. At shorter distances from the junction, the smaller modes with smaller particle volumes were dominant across the stream cross‐sections. A systematic shift towards larger particle sizes and larger particle volumes occurred downstream. The analysis of laboratory PSDs for Azufre/Caracarani mixing ratios between 0.01 and 0.5 (pH from 6.2 to 2.3) showed a bimodal trend with ~15 and 50 μm characteristic diameters; larger particles formed at pH>4. When particle suspensions were transferred in laboratory experiments from very low pH to full mixing conditions (pH ~ 2.8 and mixing ratio ~ 0.25) particle sizes varied, and the dissolved arsenic concentration decreased. The observed reaction kinetics were slow compared to the time scale of advective transport, creating opportunities for engineered controls for arsenic. This work contributes to a better understanding of the chemical‐hydrodynamic interactions in watersheds affected by mining, and identifying opportunities to improve water quality at points of use.     

ISA model: A constitutive model for soils with yield surface in the intergranular strain space

In this article, a new constitutive model for soils is proposed. It is formulated by means of plasticity, but in contrast to the precedent works, it presents a yield function describing a surface within the intergranular strain space. This latter is a state variable providing information of the recent strain history. An expression for the plastic strain rate has been proposed to guarantee the stress rate continuity. Under the application of medium or large strain amplitudes, the constitutive equation becomes independent of the intergranular strain and delivers a mathematical structure similar to some Karlsruhe hypoplastic models. Some simulations of monotonic and cyclic triaxial test are provided to evaluate and analyze the model performance. Copyright © 2015 John Wiley & Sons, Ltd.