Antagonistic Potential of Native Trichoderma spp. against Phytophthora cinnamomi in the Control of Holm Oak Decline in Dehesas Ecosystems

Phytophthora root rot caused by the pathogen Phytophthora cinnamomi is one of the main causes of oak mortality in Mediterranean open woodlands, the so-called dehesas. Disease control is challenging; therefore, new alternative measures are needed. This study focused on searching for natural biocontrol agents with the aim of developing integrated pest management (IPM) strategies in dehesas as a part of adaptive forest management (AFM) strategies. Native Trichoderma spp. were selectively isolated from healthy trees growing in damaged areas by P. cinnamomi root rot, using Rose Bengal selective medium. All Trichoderma (n = 95) isolates were evaluated against P. cinnamomi by mycelial growth inhibition (MGI). Forty-three isolates presented an MGI higher than 60%. Twenty-one isolates belonging to the highest categories of MGI were molecularly identified as T. gamsii, T. viridarium, T. hamatum, T. olivascens, T. virens, T. paraviridescens, T. linzhiense, T. hirsutum, T. samuelsii, and T. harzianum. Amongst the identified strains, 10 outstanding Trichoderma isolates were tested for mycoparasitism, showing values on a scale ranging from 3 to 4. As far as we know, this is the first report referring to the antagonistic activity of native Trichoderma spp. over P. cinnamomi strains cohabiting in the same infected dehesas. The analysis of the tree health status and MGI suggest that the presence of Trichoderma spp. might diminish or even avoid the development of P. cinnamomi, protecting trees from the worst effects of P. cinnamomi root rot

Intimate Partner Aggression Committed by Prison Inmates With Psychopathic Profile

[Abstract] Psychopathy and intimate partner aggression (IPA) are two concepts that usually appear concomitantly. Male violence toward women is often considered a psychopathic trait that sometimes involves the woman’s homicide by her partner and, at other times, attempted homicide. This phenomenon has been studied by conducting interviews following Hare’s model with 92 men incarcerated under a compliance regime in a Spanish prison (Córdoba). The results detected six explanatory factors of IPA as a result of attempted homicide or homicide: criminal past and delinquency, impulsivity, the need to stand out from others, lack of empathy, manipulation of others, and instability in partner relationships. The first two factors predict a occurrence of high scores on Hare’s Psychopathy Checklist. The results are discussed, and future lines of research are presented, especially focused on the concept of dehumanization and reveng

Periodicity and chaos on a modified Samuelson model

Several discrete time nonlinear growth models with complicated dynamical behavior have been introduced in the literature. In this paper we propuse a modified Samuelson model and we study its dynamical behavior depending on several parameters, which turn out to be the same as the logistic family. Moreover in the base situation the dynamical behavior only depends on the initial values of supply and demand

Expectativas del Mercado y Creación de Valor en la Empresa

El presente artículo propone un modelo de valoración para empresas cotizadas en bolsa, teniendo en cuenta dos posibles tipos de inversiones: - Inversiones antiguas: Son las inversiones que están en relación con el negocio tradicional de la empresa. - Inversiones nuevas: Son las inversiones que no están en relación con el negocio tradicional de la empresa. A través de estos dos tipos de inversión se formula un modelo, donde se consideran para cada una de ellos las siguientes variables. - Antiguas inversiones: Flujos de caja, reinversiones de los mismos y rentabilidades esperadas. - Nuevas inversiones: Flujos de caja, reinversiones de los mismos y rentabilidades esperadas

A MEC-IIoT intelligent threat detector based on machine learning boosted tree algorithms

In recent years, new management methods have appeared that mark the beginning of a new industrial revolution called Industry 4.0 or the Industrial Internet of Things (IIoT). IIoT brings together new emerging technologies, such as the Internet of Things (IoT), Deep Learning (DL) and Machine Learning (ML), that contribute to new applications, industrial processes and efficiency management in factories. This combination of new technologies and contexts is paired with Multi-access Edge Computing (MEC) to reduce costs through the virtualisation of networks and services. As these new paradigms increase in growth, so does the number of threats and vulnerabilities, making IIoT a very desirable target for cybercriminals. In addition, IIoT devices have certain intrinsic limitations, especially due to their limited resources, and this makes it impossible, in many cases, to detect attacks by using solutions designed for other paradigms. So it is necessary to design, implement and evaluate new solutions or adapt existing ones. Therefore, this paper proposes an intelligent threat detector based on boosted tree algorithms. Such detectors have been implemented and evaluated in an environment specifically designed to test IIoT deployments. In this way, we can learn how these algorithms, which have been successful in multiple contexts, behave in a paradigm with known constraints. The results obtained in the study show that our intelligent threat detector achieves a mean efficiency of between 95%–99% in the F1 Score metric, indicating that it is a good option for implementation in these scenarios

Corpus based learning of stochastic, context-free grammars combined with Hidden Markov Models for tRNA modelling

[EN] In this paper, a new method for modelling tRNA secondary structures is presented. This method is based on the combination of stochastic context-free grammars (SCFG) and Hidden Markov Models (HMM). HMM are used to capture the local relations in the loops of the molecule (nonstructured regions) and SCFG are used to capture the long term relations between nucleotides of the arms (structured regions). Given annotated public databases, the HMM and SCFG models are learned by means of automatic inductive learning methods. Two SCFG learning methods have been explored. Both of them take advantage of the structural information associated with the training sequences: one of them is based on a stochastic version of the Sakakibara algorithm and the other one is based on a Corpus based algorithm. A final model is then obtained by merging of the HMM of the nonstructured regions and the SCFG of the structured regions. Finally, the performed experiments on the tRNA sequence corpus and the non-tRNA sequence corpus give significant results. Comparative experiments with another published method are also presented.We would like to thank Diego Linares and Joan Andreu Sanchez for answering all our questions about SCFG, as well as Satoshi Sekine for his evaluation software. We would also like to thank the Ministerio de Sanidad y Consumo of Spain for the grants to the INBIOMED consortium.García Gómez, JM.; Benedí Ruiz, JM.; Vicente Robledo, J.; Robles Viejo, M. (2005). Corpus based learning of stochastic, context-free grammars combined with Hidden Markov Models for tRNA modelling. International Journal of Bioinformatics Research and Applications. 1(3):305-318. doi:10.1504/IJBRA.2005.007908S3053181

Physical Activity Practice, Sleeping Habits and Academic Achievement

There is a wide body of research that has identified the strong links between health behaviors and academic achievement. The media and official agencies strive to convey to schoolchildren and the public the need to show healthy lifestyles. However, it is striking that sleep habits have been considered in few occasions within healthy behaviors to be developed and promoted. Schools should encourage their students to be active because the effect of physical exercise will promote sleep and will positively affect the performance of academic tasks. Then, it is necessary to revitalize and establish the subject of Physical Education and Sport practice properly where the students can meet a minimum of 150 minutes of moderate-to-vigorous exercise per week. This approach will have a direct impact on the school children’s performance and health. Therefore, the key question is to decide whether educational centers must promote active lifestyles where sleep and exercise will be promoting or maintain schools where the body and body intelligence remain an irrelevant matter

Anthropometric measures as predictive indicators of metabolic risk in a population of “holy week costaleros”

Preventive measures are a priority in those groups that perform intense physical efforts without physical preparation and that can also be overweight or obese. One of the groups that reflect these characteristics is the costaleros of the Holy Week of Andalusia, Spain. This paper aims to describe the effect of obesity on blood pressure. A descriptive cross-sectional study was conducted on 101 costaleros. The anthropometric measures were determined through segmental impedance. Cardiac recovery and anaerobic power were measured through the Ruffier–Dickson test and the Abalakov test, respectively. Blood pressure was measured when the individuals were at rest. The Kruskal–Wallis test was applied for of continuous parameters and the X2 test for dichotomous measures. Binary logistic regression models were used for the subsequent analysis with R-square and Receiver Operating Characteristic (ROC) curves. The average population was 28 years of age, 173.7 cm tall, and 82.59 Kg weigh. The excess of body fat was 11.27 Kg and Body Mass Index was 27.33 Kg/m2. 72.3% showed abnormal blood pressure and 68.2% were overweight. 32.7% had a waist-hip ratio higher than 0.94. The probability of presenting abnormal blood pressure was higher among the subjects whose fat content was higher and muscle content was lower

Ranking Semantic Web Services Using Rules Evaluation and Constraint Programming

Current Semantic Web Services discovery and ranking proposals are based on user preferences descriptions whose expressiveness are limited by the underlying logical formalism used. Thus, highly expressive preference descriptions, such as utility functions, cannot be handled by the kind of reasoners traditionally used to perform Semantic Web Services tasks. in this work, we outline a hybrid approach to allow the introduction of utility functions in user preferences descriptions, where both rules evaluation and constraint programming are used to perform the ranking process. Our proposal extends the Web Service Modeling Ontology with these descriptions, providing a highly expressive framework to specify preferences, and enabling a more general ranking process, which can be performed by different engines

Analysis of Immunotherapy in hepatocellular carcinoma

One reason immunotherapy is important for Hepatocellular carcinoma, it’s because there are many immune cells in that organ. Because HCC is very aggressive, immunotherapy must be applied correctly. There are a lot of immunotherapies for all cancers, nevertheless, some has been tested for specific organs or tissues, and probably in the future, this organ-specific treatments can be applied in other tumor tissues.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech