Semiclassical methods in molecular collisions

Part 1 A classical path method using hyperbolic orbits and perturbation theory has been used to calculate rotational excitation cross sections for polar-ion-electron collisions. Good agreement with corresponding Coulomb-Born calculations is obtained close to threshold. The focussing effect of the Coulomb field is shown to be important for close collisions. Previous calculations including the dipole potential only are shown to underestimate substantially the ∆J = +1 rotational cross section particularly for weak dipoles. Calculations using the quadrupole interaction only are shown to be unreliable. Cross sections including an empirical estimate of short- range effects have been performed for HD+, CH+ and H30+ at electron energies up to a few electron volts. Part 2 The Strong Coupling Correspondence Principle (SCCP) method is applied to rotationally inelastic HF-HF and HC1-HC1 collisions. Transitions probabilities and cross sections have been calculated for different transitions and energies. Good agreement with corresponding quantum mechanical close coupling (CC) is found only for some transitions. Comparison with other theories suggests ti.at all theories are unreliable for adiabatic collisions. The first-order correspondence principle (FOCP) is consistently unreliable, overestimating the transition probability. The body-fixed correspondence principle (BFCP) approximation, the M-conserving correspondence principle (MCCP) and the decoupled-L-dominant correspondence principle (DLDCP) approximation are derived and applied to the molecule-molecule collision. Comparison with SCCP shows that MCCP is the better approximation. BFCP is good for short-range adiabatic collisions while DLDCP is good at large impact parameters only for some transitions

Casimir pistons with generalized boundary conditions: a step forward

In this work we study the Casimir effect for massless scalar fields propagating in a piston geometry of the type $I\times N$ where $I$ is an interval of the real line and $N$ is a smooth compact Riemannian manifold. Our analysis represents a generalization of previous results obtained for pistons configurations as we consider all possible boundary conditions that are allowed to be imposed on the scalar fields. We employ the spectral zeta function formalism in the framework of scattering theory in order to obtain an expression for the Casimir energy and the corresponding Casimir force on the piston. We provide explicit results for the Casimir force when the manifold $N$ is a $d$-dimensional sphere and a disk.Comment: 27 pages and 5 figures. A new section has been added. To appear in Analysis and Mathematical Physic

Casimir Energy for concentric δ\delta-δ′\delta' spheres

We study the vacuum interaction of a scalar field and two concentric spheres defined by a singular potential on their surfaces. The potential is a linear combination of the Dirac-$\delta$ and its derivative. The presence of the delta prime term in the potential causes that it behaves differently when it is seen from the inside or from the outside of the sphere. We study different cases for positive and negative values of the delta prime coupling, keeping positive the coupling of the delta. As a consequence, we find regions in the space of couplings, where the energy is positive, negative or zero. Moreover, the sign of the $\delta'$ couplings cause different behavior on the value of the Casimir energy for different values of the radii. This potential gives rise to general boundary conditions with limiting cases defining Dirichlet and Robin boundary conditions what allows us to simulate purely electric o purely magnetic spheres.Comment: 9 pages, 8 figures We are submitting this manuscript for publication in Physical Review

Retrieval of Boost Invariant Symbolic Observables via Feature Importance

Deep learning approaches for jet tagging in high-energy physics are characterized as black boxes that process a large amount of information from which it is difficult to extract key distinctive observables. In this proceeding, we present an alternative to deep learning approaches, Boost Invariant Polynomials, which enables direct analysis of simple analytic expressions representing the most important features in a given task. Further, we show how this approach provides an extremely low dimensional classifier with a minimum set of features representing %effective discriminating physically relevant observables and how it consequently speeds up the algorithm execution, with relatively close performance to the algorithm using the full information

Fast oxidation of the neonicotinoid pesticides listed in the EU Decision 2018/840 from aqueous solutions

Neonicotinoid pesticides family is nowadays identified as the most important type of insecticides in the world. Their consequent widespread occurrence in the environment represents not only a well-known risk for bees but also a significant negative impact in aquatic ecosystems. In this work, the capability of catalytic wet peroxide oxidation (CWPO) (Fe3O4-R400/H2O2) as a low-cost and environmentally-friendly system for the treatment of the neonicotinoid pesticides listed in the EU Watch List (Decision 2018/840) (acetamiprid (ACT), clothianidin (CLT), imidacloprid (IMD), thiacloprid (THC) and thiamethoxam (THM)) has been investigated. Remarkably, complete elimination of the pollutants (1000 g L-1)and the aromatic by-products was reached in 20 min reaction time operating at 25 °C, 1 atm, and pH0 = 5,, with the stoichiometric H2O2 amount (~4 – 5 mg L-1) and 1 g L-1 catalyst load. The reactivity order of the insecticides decreased as follows: THC>IMD>THM>CLT>ACT, being the pseudo-first order rate constant values within the range of 0.26 – 0.61 min-1. Notably, high mineralization yields were obtained (>50%) being the final effluents non-toxic. As example, the oxidation pathway of ACT was proposed. Finally, the catalytic system was tested in real surface waterThis research has been founded by the CTM2016-76454-R project (Spanish MINECO) and by the S2013/MAE-2716 project (CM). M. Munoz thanks the postdoctoral Ramón y Cajal contract (RYC-2016-20648) to the Spanish MINEC

Predicting Beta Decay Energy with Machine Learning

$Q_\beta$ represents one of the most important factors characterizing unstable nuclei, as it can lead to a better understanding of nuclei behavior and the origin of heavy atoms. Recently, machine learning methods have been shown to be a powerful tool to increase accuracy in the prediction of diverse atomic properties such as energies, atomic charges, volumes, among others. Nonetheless, these methods are often used as a black box not allowing unraveling insights into the phenomena under analysis. Here, the state-of-the-art precision of the $\beta$-decay energy on experimental data is outperformed by means of an ensemble of machine-learning models. The explainability tools implemented to eliminate the black box concern allowed to identify uncertainty and atomic number as the most relevant characteristics to predict $Q_\beta$ energies. Furthermore, physics-informed feature addition improved models' robustness and raised vital characteristics of theoretical models of the nuclear structure

Health economics: identifying leading producers, countries relative specialization and themes

El área de investigación en economía de la salud tuvo una gran evolución a partir de la década de 1960 y está en constante crecimiento. Actualmente, el gasto en salud es un tema clave en todo el mundo. La bibliometría proporciona varios métodos para explorar el impacto y la evolución de la investigación. Así pues, el principal objetivo del presente estudio es comprender la situación actual de la investigación en materia de economía de la salud para el período 2010-2019. Se analizaron tres aspectos diferentes: la producción de los países, el índice de prioridad relativa y los temas principales. El conjunto de datos se obtuvo a partir de los documentos indizados en la base de datos Web of Science de 2010 a 2019. Se utilizó el software SciMAT para obtener el análisis temático mediante el análisis de mapas de la ciencia. Las revistas Health economics, Value in Health, Journal of Health Economics y European Journal of Health Economics son los principales productoras. Estados Unidos, Inglaterra y Alemania son los que tienen una mayor producción; los Países Bajos, Inglaterra y Australia son los que tienen el índice de prioridad relativa más alto. Los años de vida ajustados en función de la calidad y la desigualdad en materia de salud son los temas con mayor número de documentos y medidas de impacto. Este estudio es un marco útil basado en ciencia que servirá de base para futuras acciones de investigación.Health economics research area was a high evolution from the 1960s and it is constantly growing. Currently, the health expenditure is a key issue worldwide. Bibliometrics provides several methods to explore the impact and evolution of the research. Thus, the main aim of the present study is to understand the current status of the research in health economics for the period 2010-2019. Three different aspects were analyzed: countries production, relative priority index and main themes. The dataset was obtained from the documents indexed in the Web of Science database from 2010 to 2019. SciMAT software was used to obtain the thematic analysis by means of science mapping analysis. The journals Health economics, Value in Health, Journal of Health Economics, and European Journal of Health Economics are the main producers. USA, England and Germany are those with highest production; Netherlands, England and Australia are those with the highest relative priority index. Quality adjusted life years and Health inequality are the themes with the highest number of documents and impact measures. This study is a useful evidence-based framework on which to base future research actions

The nutritional impact of replacing dietary meat with meat alternatives in the UK: a modelling analysis using nationally representative data

Dietary patterns high in meat compromise both planetary and human health. Meat-alternatives may help facilitate meat reduction, however the nutritional implications of displacing meat with meat-alternatives does not appear to have been evaluated. Here, data from the 9th cycle of the National Diet and Nutrition Survey was used as the basis of models to assess the effect of meat substitution on nutritional intake. We implemented three models; model 1 progressively replaced 25%, 50%, 75%, or 100% of the current meat intake with a weighted mean of meat-alternatives available in the UK market. Model 2 compared different ingredient categories of meat-alternative; vegetable, mycoprotein, a combination of bean and pea, tofu, nut and soy. Model 3 compared fortified versus unfortified meat-alternatives. The models elicited significant shifts in nutrients. Overall, there were increases in carbohydrate, fibre, sugars and sodium, whereas reductions were found for protein, total and saturated fat, iron and B12. The greatest effects were seen for; vegetable-based (+24.63g/day carbohydrates), mycoprotein-based (−6.12g/day total fat), nut-based (−19.79g/day protein, +10.23g/day fibre; −4.80g/day saturated fat, +7.44g/day sugars), soy-based (+495.98mg/day sodium), and tofu-based (+7.63mg/day iron, −2.02μg/day B12). Our results suggest meat-alternatives can be a healthful replacement for meat if chosen correctly. Consumers should seek out meat-alternatives which are low in sodium and sugar, high in fibre, protein and with high micronutrient density, to avoid compromising nutritional intake if reducing their meat intake. Manufacturers and policy makers should consider fortification of meat-alternatives with nutrients such as iron and B12 and focus on reducing sodium and sugar content