Spin dynamics of current driven single magnetic adatoms and molecules

A scanning tunneling microscope can probe the inelastic spin excitations of a single magnetic atom in a surface via spin-flip assisted tunneling in which transport electrons exchange spin and energy with the atomic spin. If the inelastic transport time, defined as the average time elapsed between two inelastic spin flip events, is shorter than the atom spin relaxation time, the STM current can drive the spin out of equilibrium. Here we model this process using rate equations and a model Hamiltonian that describes successfully spin flip assisted tunneling experiments, including a single Mn atom, a Mn dimer and Fe Phthalocyanine molecules. When the STM current is not spin polarized, the non-equilibrium spin dynamics of the magnetic atom results in non-monotonic $dI/dV$ curves. In the case of spin polarized STM current, the spin orientation of the magnetic atom can be controlled parallel or anti-parallel to the magnetic moment of the tip. Thus, spin polarized STM tips can be used both to probe and to control the magnetic moment of a single atom.Comment: 15 pages, 12 figure

Storage of classical information in quantum spins

Digital magnetic recording is based on the storage of a bit of information in the orientation of a magnetic system with two stable ground states. Here we address two fundamental problems that arise when this is done on a quantized spin: quantum spin tunneling and back-action of the readout process. We show that fundamental differences exist between integer and semi-integer spins when it comes to both, read and record classical information in a quantized spin. Our findings imply fundamental limits to the miniaturization of magnetic bits and are relevant to recent experiments where spin polarized scanning tunneling microscope reads and records a classical bit in the spin orientation of a single magnetic atom

Squeezed States and Helmholtz Spectra

The 'classical interpretation' of the wave function psi(x) reveals an interesting operational aspect of the Helmholtz spectra. It is shown that the traditional Sturm-Liouville problem contains the simplest key to predict the squeezing effect for charged particle states.Comment: 10 pages, Latex, 3 gzip-compressed figures in figh.tar.g

Landslide Susceptibility Mapping of Landslides with Artificial Neural Networks: Multi-Approach Analysis of Backpropagation Algorithm Applying the Neuralnet Package in Cuenca, Ecuador

Los riesgos o amenazas naturales generan desastres y enormes pérdidas en varios aspectos, siendo los deslizamientos de tierra uno de los que han causado mayores impactos a nivel mundial. El objetivo de esta investigación fue explorar un método basado en aprendizaje automático para evaluar la susceptibilidad a deslizamientos rotacionales en una zona cercana a la ciudad de Cuenca, Ecuador, que presenta una alta incidencia de estos fenómenos, principalmente por sus condiciones ambientales, y en la que, sin embargo, estos estudios son escasos. El método implementado consistió en una red neuronal artificial de tipo perceptrón multicapa (ANN MLP), generado con el paquete neuralnet R, con el que se generaron cinco mapas de susceptibilidad a deslizamientos (LSM) para el área de estudio, empleando diferentes algoritmos de retropropagación (RPROP+, RPROP−, SLR, SAG y Backprop). Se consideró un inventario de deslizamientos actualizado a 2019 y 10 factores condicionantes, principalmente topográficos, geológicos, de cobertura del suelo e hidrológicos. Los resultados obtenidos, que fueron validados mediante el valor del área bajo la curva ROC (AUC-ROC) y los parámetros estadísticos de precisión (precision), sensibilidad o recuerdo (recall), exactitud (accuracy) y F-Score, mostraron un buen grado de ajuste y una capacidad predictiva aceptable. Los mapas resultantes mostraron que la zona tiene en su mayoría sectores de susceptibilidad moderada, alta y muy alta, cuyos porcentajes de ocurrencia de deslizamientos varían entre aproximadamente el 63% y el 80%. En esta investigación se implementaron diferentes variantes del algoritmo de retropropagación para verificar cuál daba mejores resultados. Con la implementación de metodologías adicionales y una correcta zonificación se podrían desarrollar futuros análisis, contribuyendo a una adecuada planificación territorial y una mejor gestión del riesgo de desastres en la zona de estudio

Analysis of Conditioning Factors in Cuenca, Ecuador, for Landslide Susceptibility Maps Generation Employing Machine Learning Methods

Landslides are events that cause great impact in different parts of the world. Their destructive capacity generates loss of life and considerable economic damage. In this research, several Machine Learning (ML) methods were explored to select the most important conditioning factors, in order to evaluate the susceptibility to rotational landslides in a sector surrounding the city of Cuenca (Ecuador) and with them to elaborate landslide susceptibility maps (LSM) by means of ML. The methods implemented to analyze the importance of the conditioning factors checked for multicollinearity (correlation analysis and VIF), and, with an ML-based approach called feature selection, the most important factors were determined based on Classification and Regression Trees (CART), Feature Selection with Random Forests (FS RF), and Boruta and Recursive Feature Elimination (RFE) algorithms. LSMs were implemented with Random Forests (RF) and eXtreme Gradient Boosting (XGBoost) methods considering a landslide inventory updated to 2019 and 15 available conditioning factors (topographic (10), land cover (3), hydrological (1), and geological (1)), from which, based on the results of the aforementioned analyses, the six most important were chosen. The LSM were elaborated considering all available factors and the six most important ones, with the previously mentioned ML methods, and were compared with the result generated by an Artificial Neural Network with resilient backpropagation (ANN rprop-) with six conditioning factors. The results obtained were validated by means of AUC-ROC value and showed a good predictive capacity for all cases, highlighting those obtained with XGBoost, which, in addition to a high AUC value (>0.84), obtained a good degree of coincidence of landslides at high and very high susceptibility levels (>72%). Despite the findings of this research, it is necessary to study in depth the methods applied for the development of future research that will contribute to developing a preventive approach in the study are

Age-structure, growth and reproduction of the introduced pumpkinseed (lepomis gibbosa, l. 1758) in a tributary of the Guadalquivir river (southern Spain)

The age structure, growth and reproduction of Lepomis gibbosa (L. 1758) (= L. gibbosus) was studied from March 1993 to September 1994 in a tributary stream of the Guadalquivir River. The maximum age observed was 5+ years both in males and females. In the O+ group, seasonal growth began in February and lasted 8 months. Males and females matured during their second year of life (l+). There were no significant differences in the overall sex-ratio, which was 1: 1.1 (677 males to 745 females). Reproductive activity started in MarcWApril and lasted until AugusUSeptember. During this period, females spawned 2 batches of eggs. The relationship between fecundity (F) and fork length (&, mm) was: F=5.09 % 279 (1993) and F=85.81 L, ' 56 (1994). The maximum contribution to the fecundity of the population was observed in the 4+ female group. The reproductive effort was maximun in the 3+ group. Compared with the American pumpkinseed populations that have been studied, the lifehistory patterns of this stock are characterized by low annual growth, early maturity, reduced longevity and low fecundity

On Weierstra{\ss} semigroups at one and two points and their corresponding Poincar\'e series

The aim of this paper is to introduce and investigate the Poincar\'e series associated with the Weierstra{\ss} semigroup of one and two rational points at a (not necessarily irreducible) non-singular projective algebraic curve defined over a finite field, as well as to describe their functional equations in the case of an affine complete intersection.Comment: Beginning of Section 3 and Subsection 3.1 were modifie

Edad y crecimiento de Barbus graellsii Steindachner, 1866 y Chondrostoma miegii, Steindachner, 1866 (Pisces, Cyprinidae) en el río Cinca (cuenca hidrográfica del Ebro, NE España)

The age and growth of two endemic cyprinids from the lberian peninsula were studied for one year in a stretch of the Cinca River. There were caught by electrofishing 279 individuals of B. graellsii and 189 individuals of Ch. miegii. lmmature specimens of both species were not caught probably due to their migratory behaviour during the reproductive period. B. graellsii presented a maximum of 11 age classes in both sexes. Female Ch. miegii live for 8 years and males seven years. Growth was allometric in B. graellsii specimens whereas Ch. miegii showed isometric growth. Females were longer than males in both species. B. graellsii females showed higher growth rates than males whereas Ch. miegii showed similar growth rates between sexes. B. graellsii males showed a significant increase in condition before the reproductive period and a decrease in condition during this period, while females only showed a significant decrease in condition in July. Ch. miegii females presented dynamics of condition very similar to B. graellsii males. Key words: Age, Growth, Cyprinidae, Barbus graellsii, Chondrostoma miegii.The age and growth of two endemic cyprinids from the lberian peninsula were studied for one year in a stretch of the Cinca River. There were caught by electrofishing 279 individuals of B. graellsii and 189 individuals of Ch. miegii. lmmature specimens of both species were not caught probably due to their migratory behaviour during the reproductive period. B. graellsii presented a maximum of 11 age classes in both sexes. Female Ch. miegii live for 8 years and males seven years. Growth was allometric in B. graellsii specimens whereas Ch. miegii showed isometric growth. Females were longer than males in both species. B. graellsii females showed higher growth rates than males whereas Ch. miegii showed similar growth rates between sexes. B. graellsii males showed a significant increase in condition before the reproductive period and a decrease in condition during this period, while females only showed a significant decrease in condition in July. Ch. miegii females presented dynamics of condition very similar to B. graellsii males. Key words: Age, Growth, Cyprinidae, Barbus graellsii, Chondrostoma miegii.The age and growth of two endemic cyprinids from the lberian peninsula were studied for one year in a stretch of the Cinca River. There were caught by electrofishing 279 individuals of B. graellsii and 189 individuals of Ch. miegii. lmmature specimens of both species were not caught probably due to their migratory behaviour during the reproductive period. B. graellsii presented a maximum of 11 age classes in both sexes. Female Ch. miegii live for 8 years and males seven years. Growth was allometric in B. graellsii specimens whereas Ch. miegii showed isometric growth. Females were longer than males in both species. B. graellsii females showed higher growth rates than males whereas Ch. miegii showed similar growth rates between sexes. B. graellsii males showed a significant increase in condition before the reproductive period and a decrease in condition during this period, while females only showed a significant decrease in condition in July. Ch. miegii females presented dynamics of condition very similar to B. graellsii males. Key words: Age, Growth, Cyprinidae, Barbus graellsii, Chondrostoma miegii

Alarm-Based Prescriptive Process Monitoring

Predictive process monitoring is concerned with the analysis of events produced during the execution of a process in order to predict the future state of ongoing cases thereof. Existing techniques in this field are able to predict, at each step of a case, the likelihood that the case will end up in an undesired outcome. These techniques, however, do not take into account what process workers may do with the generated predictions in order to decrease the likelihood of undesired outcomes. This paper proposes a framework for prescriptive process monitoring, which extends predictive process monitoring approaches with the concepts of alarms, interventions, compensations, and mitigation effects. The framework incorporates a parameterized cost model to assess the cost-benefit tradeoffs of applying prescriptive process monitoring in a given setting. The paper also outlines an approach to optimize the generation of alarms given a dataset and a set of cost model parameters. The proposed approach is empirically evaluated using a range of real-life event logs