Relativistic Quantum Scattering of High Energy Fermions in the Presence of Phase Transition

We study the high energy behaviour of fermions hitting a general wall caused by a first-order phase transition. The wall profile is introduced through a general analytic function. The reflection coefficient is computed in the high energy limit and expressed in terms of the poles of the wall profile function. It is shown that the leading singularity gives the high energy behaviour.Comment: 10 page

Sleep Duration is Inversely Associated with Serum Uric Acid Concentrations and Uric Acid to Creatinine Ratio in an Elderly Mediterranean Population at High Cardiovascular Risk

The aim of the study was to evaluate sleep duration and sleep variability in relation to serum uric acid (SUA) concentrations and SUA to creatinine ratio. This is a cross-sectional analysis of baseline data from 1842 elderly participants with overweight/obesity and metabolic syndrome in the (Prevención con Dieta Mediterránea) PREDIMED-Plus trial. Accelerometry-derived sleep duration and sleep variability were measured. Linear regression models were fitted to examine the aforementioned associations. A 1 hour/night increment in sleep duration was inversely associated with SUA concentrations (β = −0.07, p = 0.047). Further adjustment for leukocytes attenuated this association (p = 0.050). Each 1-hour increment in sleep duration was inversely associated with SUA to creatinine ratio (β = −0.15, p = 0.001). The findings of this study suggest that longer sleep duration is associated with lower SUA concentrations and lower SUA to creatinine ratio.Instituto de Salud Carlos III Fondo de Investigación para la Salud (FIS)European Regional Development Fund (FEDER)European Research Council (Advanced Research Grant 2013–2018; 340918)Consejería de Salud de la Junta de AndalucíaGeneralitat ValencianaGeneralitat de Catalunya (PERIS 2016–2020 Incorporació de Científics I Tecnòlegs, SLT002/0016/00428)Servicio Andaluz de Salud (SAS) (B-0003-2017

Performance evaluation of the Hilbert–Huang transform for respiratory sound analysis and its application to continuous adventitious sound characterization

© 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/The use of the Hilbert–Huang transform in the analysis of biomedical signals has increased during the past few years, but its use for respiratory sound (RS) analysis is still limited. The technique includes two steps: empirical mode decomposition (EMD) and instantaneous frequency (IF) estimation. Although the mode mixing (MM) problem of EMD has been widely discussed, this technique continues to be used in many RS analysis algorithms. In this study, we analyzed the MM effect in RS signals recorded from 30 asthmatic patients, and studied the performance of ensemble EMD (EEMD) and noise-assisted multivariate EMD (NA-MEMD) as means for preventing this effect. We propose quantitative parameters for measuring the size, reduction of MM, and residual noise level of each method. These parameters showed that EEMD is a good solution for MM, thus outperforming NA-MEMD. After testing different IF estimators, we propose Kay¿s method to calculate an EEMD-Kay-based Hilbert spectrum that offers high energy concentrations and high time and high frequency resolutions. We also propose an algorithm for the automatic characterization of continuous adventitious sounds (CAS). The tests performed showed that the proposed EEMD-Kay-based Hilbert spectrum makes it possible to determine CAS more precisely than other conventional time-frequency techniques.Postprint (author's final draft

The Next Vaccine Generation Against Malaria: Structurally Modulated Plasmodium Antigens

Challenges for obtaining more effective malaria vaccines depend on precise selection of antigenic motifs and understanding the complexity of Plasmodium spp. life cycle. Naturally expressed antigens are characterized for being weak immunogenic when tested as vaccine components, thus these have to be strategically modified to render them immunogenic. A molecular clue in this pursuit is provided by the chemical peptide-bond processing by peptidases, which follows a multistep pathway including ephemeral high energy molecular complexes known as transition states. Thus, we have proposed non-natural peptide-bond isosteres as transition states mimetics, and therefore, stabilizing these high-energy states with site-directed designed immuno-mimetics have demonstrated being a rational approach for stimulating antibody populations harboring multiple functional capacities. Therefore, peptide-bond substitutes constitute a coherent pathway towards obtaining selected immuno-active compounds from specific plasmodial molecular objectives. Chemical strategies for synthesizing peptido-mimetics and antimalarial selected trials lead us to assess a number of peptide-bond substitutes for obtaining immuno-active and structurally defined molecules. Plasmodium antigens expressed on merozoite, sporozoite and gametocyte stages have been selected as targets and subsequently modified based on the presence of either a high-binding motif or a potential HLA-reading frame. This new family of immuno-mimetics is and efficient neutralizing antibody inducers when tested in in vitro and in vivo experiments, thus representing a new generation of malaria vaccine components

Efficiency of European banking systems: A correction by environment variables

In this paper we extend the efficiency cross-country comparisons to ten European countries in order to know how different or similar current banking performances are. We start with two types of comparisons. First of all, we evaluate the average technical efficiency of each country by means of a DEA model called "basic" model. This model includes only banking variables. Our second model, called "complete", does consider environmental variables together with the banking variables of the basic model. The empirical results recommended us to substitute the original environmental variables with new codified variables. Finally, the non homogeneity of the country-samples, observed after performing an individual DEA analysis for each country, was decisive for considering two new models, based on a modified sample. The comparisons between the last two models show that the country specific environmental conditions exercise a strong influence over the average efficiency score of each country. El objetivo de este trabajo es comparar la eficiencia de diez países europeos. Para ello, el trabajo comienza con dos tipos de modelos. El primero analiza la eficiencia técnica media de cada país por medio de un modelo DEA que denominamos “modelo básico” y que incluye sólo variables bancarias. El segundo, llamado “modelo completo” incluye variables ambientales junto con las variables bancarias del modelo básico. Los resultados obtenidos en este segundo modelo recomendaron sustituir las variables ambientales originales por unas nuevas variables codificadas. Finalmente, la heterogeneidad de las muestras por países, observada después de realizar un análisis individual por país, lleva a considerar dos nuevos modelos, basados ambos en el modelo codificado. Las comparaciones entre estos dos modelos muestran que las condiciones ambientales de cada país ejercen una influencia muy fuerte en la eficiencia media de cada país.Eficiencia, DEA, condiciones ambientales, banca europea Efficiency, DEA, environmental conditions, European banking

Electronic Noses Applications in Beer Technology

This chapter describes and explains in detail the electronic noses (e-noses) as devices composed of an array of sensors that measure chemical volatile compounds and apply classification or regression algorithms. Then, it reviews the most significant applications of such devices in beer technology, with examples about defect detection, hop classification, or beer classification, among others. After the review, the chapter illustrates two applications from the authors, one about beer classification and another about beer defect detection. Finally, after a comparison with other analytical techniques, the chapter ends with a summary, conclusions, and the compelling future of the e-noses applied to beer technology

Systematic Review: Preventive Intervention to Curb the Youth Online Gambling Problem

This systematic review focuses on all the gambling addiction prevention programs carried out in schools, with the intention of making their effectiveness known and encouraging the creation of more such programs. During the third quarter of 2021, an exhaustive search was conducted using the databases of Scopus, Medline (via Pubmed), WOS, and PsycINFO. The search strategy was based on a combination of specific search terms: “Gambling Disorder [Mesh]”, “Online Gambling Disorder [Mesh]”, and “Prevention Programs [Mesh]”. A total of 15 articles were chosen for systematic review. All the programs analyzed show effective results, although there are several methodological shortcomings in the way they are conducted. Effective programs need to focus more on long-term results and the emotional aspects of gambling. We need professionals who can convey the causal nature of the problem the youth are facing

SCMFTS: Scalable and Distributed Complexity Measures and Features for Univariate and Multivariate Time Series in Big Data Environments

This research has been partially funded by the following grants: TIN2016-81113-R from the Spanish Ministry of Economy and Competitiveness, P12-TIC-2985 and P18-TP-5168 from Andalusian Regional Government, Spain, and EU Commission with FEDER funds. Francisco J. Baldan holds the FPI grant BES-2017-080137 from the Spanish Ministry of Economy and Competitiveness. D. Peralta is a Postdoctoral Fellow of the Research Foundation of Flanders (170303/12X1619N). Y. Saeys is an ISAC Marylou Ingram Scholar.Time series data are becoming increasingly important due to the interconnectedness of the world. Classical problems, which are getting bigger and bigger, require more and more resources for their processing, and Big Data technologies offer many solutions. Although the principal algorithms for traditional vector-based problems are available in Big Data environments, the lack of tools for time series processing in these environments needs to be addressed. In this work, we propose a scalable and distributed time series transformation for Big Data environments based on well-known time series features (SCMFTS), which allows practitioners to apply traditional vector-based algorithms to time series problems. The proposed transformation, along with the algorithms available in Spark, improved the best results in the state-of-the-art on the Wearable Stress and Affect Detection dataset, which is the biggest publicly available multivariate time series dataset in the University of California Irvine (UCI) Machine Learning Repository. In addition, SCMFTS showed a linear relationship between its runtime and the number of processed time series, demonstrating a linear scalable behavior, which is mandatory in Big Data environments. SCMFTS has been implemented in the Scala programming language for the Apache Spark framework, and the code is publicly available.Spanish Government TIN2016-81113-R BES-2017-080137Andalusian Regional Government, Spain P12-TIC-2985 P18-TP-5168European Commission European Commission Joint Research Centre European Commissio

Complexity Measures and Features for Times Series classification

Classification of time series is a growing problem in different disciplines due to the progressive digitalization of the world. Currently, the state-of-the-art in time series classification is dominated by The Hierarchical Vote Collective of Transformation-based Ensembles. This algorithm is composed of several classifiers of different domains distributed in five large modules. The combination of the results obtained by each module weighed based on an internal evaluation process allows this algorithm to obtain the best results in state-of-the-art. One Nearest Neighbour with Dynamic Time Warping remains the base classifier in any time series classification problem for its simplicity and good results. Despite their performance, they share a weakness, which is that they are not interpretable. In the field of time series classification, there is a tradeoff between accuracy and interpretability. In this work, we propose a set of characteristics capable of extracting information on the structure of the time series to face time series classification problems. The use of these characteristics allows the use of traditional classification algorithms in time series problems. The experimental results of our proposal show no statistically significant differences from the second and third best models of the state-of-the-art. Apart from competitive results in accuracy, our proposal is able to offer interpretable results based on the set of characteristics proposed.Spanish Government TIN2016-81113-R PID2020-118224RB-I00 BES-2017-080137Andalusian Regional Government, Spain P12-TIC-2958 P18-TP-5168 A-TIC-388-UGR-1

Cationic Peptides Harboring Antibiotic Capacity are Selective for Leishmania panamensis and Leishmania major

The fairly recent appearance of Leishmania resistance to currently-used therapy has led to the search for new therapeutic strategies. This work was thus aimed at evaluating the in vitro effect of 18 cationic synthetic antimicrobial peptides for antileishmanial and cytotoxic and haemolytic activity. The viability of murine (J774) and human (U937), peripheral blood monocytes, HeLa and HepG2 cells and L. (V) panamensis and L. (L) major promastigotes was then ascertained using the aforementioned peptides. All antimicrobial peptides were synthesised and each cell and parasite line was treated with different peptide concentrations. Melittin, bombinin, mastoparan 8 (MP-8), MP-X and dermaseptin-S1 reduced human and murine host cells' viability at greater concentrations than pentamidine isethionate, human peripheral blood and U937 monocytes being the most sensitive to peptide action. Melittin had a toxic effect on all the cells evaluated in this study and L. (L) major was more sensitive than L. (V) panamensis to peptide effect. As MP-8, bombinin, dermaseptin-S1 and tracheal antimicrobial peptide (TAP) were active against both parasite species, and tachyplesin 1 and polystes MA selectively so for L. (L) major, they were selected as being promising as they had a >1 selectivity index (SI) and greater than 50 μg/mL haemolytic concentration (HC50), suggesting that they should continue to be studied in in vitro and in vivo infection assays as there have been no previous reports of MP-8, bombinin, TAP and Polystes MA activity regarding L. (V) panamensis and L. (L) major. © 2014 Lozano JM, et al