Genetic learning of accurate and compact fuzzy rule based systems based on the 2-tuples linguistic representation

One of the problems that focus the research in the linguistic fuzzy modeling area is the trade-off between interpretability and accuracy. To deal with this problem, different approaches can be found in the literature. Recently, a new linguistic rule representation model was presented to perform a genetic lateral tuning of membership functions. It is based on the linguistic 2-tuples representation that allows the lateral displacement of a label considering an unique parameter. This way to work involves a reduction of the search space that eases the derivation of optimal models and therefore, improves the mentioned trade-off. Based on the 2-tuples rule representation, this work proposes a new method to obtain linguistic fuzzy systems by means of an evolutionary learning of the data base a priori (number of labels and lateral displacements) and a simple rule generation method to quickly learn the associated rule base. Since this rule generation method is run from each data base definition generated by the evolutionary algorithm, its selection is an important aspect. In this work, we also propose two new ad hoc data-driven rule generation methods, analyzing the influence of them and other rule generation methods in the proposed learning approach. The developed algorithms will be tested considering two different real-world problems.Spanish Ministry of Science and Technology under Projects TIC-2002-04036-C05-01 and TIN-2005-08386-C05-0

Impact of woody semi-natural habitats on the abundance and diversity of green lacewings in olive orchards

Habitat management is a conservation biological control technique which helps to reduce the use of inputs in olive orchards and also to improve sustainability. Recent studies of olive orchards have pointed out that vegetation cover, which provides food resources, as well as reproduction and refuge sites, increases Chrysopidae populations and diversity. However, little is known about the effect of woody semi-natural habitats (SNHs) in olive orchards. In this context, our study aims to determine the attraction of adult Chrysopidae to different tree species in SNHs adjacent to olive orchards in order to promote the conservation biological control of this key predator. We vacuumed 75 almond, oak, olive and pine trees fortnightly between April and October of 2016. The trees were chosen at random and evenly distributed among five organic olive orchards selected according to their availability. Oak trees recorded the highest abundance, species richness and diversity levels of adult Chrysopidae, while olive trees had the highest abundance of Chrysopidae larvae. A total of 20 green lacewing species, belonging to seven different genera, were collected, of which Chrysoperla mutata (McLachlan, 1898), Chrysoperla pallida Henry et al., 2002 and Pseudomallada (prasinus) pp3 (Duelli and Henry, 2020) were the most abundant during the period of the study and had a preference for olive trees (C. mutata and C. pallida) and oak trees P. (prasinus) pp3. Furthermore, the number of Chrysopidae larvae collected showed a positive correlation with the percentage of predated eggs in the anthophagous and carpophagous generations of Prays oleae.Junta de Andalucia P12-AGR-141

Local management and landscape composition affect predatory mites in European wine-growing regions

Sustainable land use in agricultural landscapes is essential to counteract the global decline of biodiversity, as well to ensure ecosystem services like natural pest control. Phytoseiid mites are key natural enemies of pest mites in vineyards but how local management and landscape context affect phytoseiid mites remains poorly known. In this study, we examined the effects of farming systems, inter-row management and landscape composition on phytoseiid mite communities in 156 vineyards across five European wine-growing regions. Our results showed that phytoseiid communities were mainly dominated by one or two phytoseiid species across Europe and that local management was a major factor affecting population densities. According to the wine-growing regions, phytoseiid mite densities benefited from integrated pest management or conventional farming compared to organic farming and from spontaneous vegetation cover compared to seeded cover crops. Moreover, mite densities benefited from increasing proportions of vineyards at the landscape scale. The farming systems effects were most likely related to the positive impact of the lower pesticide use in integrated and conventional vineyards. The positive effect of spontaneous vegetation cover could be related to a better supply of nutritive pollen as food resource compared to seeded cover crops, which depends on the plant species in the inter-row. Our findings indicated accordingly that a reduced pesticide use, and inter-row management are crucial factors for promoting pest control by predatory mites in European vineyards. Moreover, the proportion of viticultural area in the landscape is a considerable factor to retain stable phytoseiid mite populations.This research was funded by the research project SECBIVIT, which was funded through the 2017-2018 Belmont Forum and BiodivERsA joint call for research proposals, under the BiodivScen ERA-Net COFUND program, with the funding organizations: Agencia Estatal de Investigación (Ministerio de ciencia e innovación/ES/Grant #10.13039/501100011033), Austrian Science Fund (AT/Grant #I 4025-B32), Federal Ministry of Education and Research and Projektträger VDI/VDE Innovation + Technik GmbH (DE), French National Research Agency (FR), Netherlands Organisation for Scientific Research (NL), National Science Foundation (US/Grant #1850943) and Romanian Executive Agency for Higher Education, Research, Development and Innovation Funding (RO)

Winegrowers’ decision-making: A pan-European perspective on pesticide use and inter-row management

European viticultural landscapes not only support a significant share of rural livelihoods and cultural traditions, but also conserve biodiversity and sustain various ecosystem services. Winegrowers' practices of inter-row management (including whether to have vegetation in the inter-rows, type of vegetation, duration of vegetation cover, and soil tillage) and pesticide use (including herbicides in the inter-rows, fungicides, insecticides, and pheromone dispensers as an alternative) can affect these services. This study aims to understand winegrowers' decision-making driven by their personal characteristics, attitudes and beliefs towards viticultural practices, physical properties of vineyards, and farm management characteristics in five European winegrowing regions. These include Palatinate in Germany, Leithaberg in Austria, Tarnave in Romania, Bordeaux in France, and Montilla-Moriles in Spain. Based on a questionnaire survey, we constructed decision trees for each behaviour per case study as well as in a generic European model. We found factors that best explain how winegrowers manage their inter-rows and use pesticides. Results showed that not only do behaviours of winegrowers vary drastically across the case studies, but also the factors that explain most behaviours: farmers' attitudes and beliefs and farm management characteristics. This implies the importance of attitudes and beliefs – which are under-researched as compared to other factors – in understanding farmers’ behaviour. With the driving factors found to vary per case study, our results also imply the need for locally-adapted policies. Furthermore, our results suggest that the effects of climate change on European viticultural landscapes concern not only shifting production regions and changes in yields, but also changing pressure of pests and diseases. Any long-term behavioural change requires efforts from many stakeholders.This research was funded by the research project SECBIVIT which was funded through the 2017–2018 Belmont Forum and BiodivERsA joint call for research proposals, under the BiodivScen ERA-Net COFUND programme, with the funding organisations: Agencia Estatal de Investigación (Ministerio de ciencia e innovación/Spain), Austrian Science Fund (FWF) (grant number I 4025-B32), Federal Ministry of Education and Research (BMBF/Germany) through VDI/VDE Innovation + Technik GmbH, DLR Projektträger, French National Research Agency (ANR), Netherlands Organisation for Scientific Research (NWO), National Science Foundation (Grant #1850943) and Romanian Executive Agency for Higher Education, Research, Development and Innovation Funding (UEFISCDI). We would like to thank all winegrowers who participated in the focus groups, online questionnaires and personal interviews and the extension services who distributed our online questionnaire through their e-mail distribution list (DLR-Rheinpfalz)

Clonal chromosomal mosaicism and loss of chromosome Y in elderly men increase vulnerability for SARS-CoV-2

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) had an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome alterations (mCA) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (mCA and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, mCA and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, individuals with clonal mosaic events (clonal mosaicism for chromosome alterations and/or loss of chromosome Y) showed an increased risk of COVID-19 lethality

Efficacy of clozapine versus standard treatment in adult individuals with intellectual disability and treatment-resistant psychosis (CLOZAID): study protocol of a multicenter randomized clinical trial

BackgroundIntellectual disability (ID) affects approximately 1% of the worldwide population and individuals with ID have a higher comorbidity with mental illness, and specifically psychotic disorders. Unfortunately, among individuals with ID, limited research has been conducted since ID individuals are usually excluded from mental illness epidemiological studies and clinical trials. Here we perform a clinical trial to investigate the effectiveness of clozapine in the treatment of resistant psychosis in individuals with ID. The article highlights the complexity of diagnosing and treating psychopathological alterations associated with ID and advocates for more rigorous research in this field.MethodsA Phase IIB, open-label, randomized, multicenter clinical trial (NCT04529226) is currently ongoing to assess the efficacy of oral clozapine in individuals diagnosed with ID and suffering from treatment-resistant psychosis. We aim to recruit one-hundred and fourteen individuals (N=114) with ID and resistant psychosis, who will be randomized to TAU (treatment as usual) and treatment-with-clozapine conditions. As secondary outcomes, changes in other clinical scales (PANSS and SANS) and the improvement in functionality, assessed through changes in the Euro-QoL-5D-5L were assessed. The main outcome variables will be analyzed using generalized linear mixed models (GLMM), assessing the effects of status variable (TAU vs. Clozapine), time, and the interaction between them.DiscussionThe treatment of resistant psychosis among ID individuals must be directed by empirically supported research. CLOZAID clinical trial may provide relevant information about clinical guidelines to optimally treat adults with ID and treatment-resistant psychosis and the benefits and risks of an early use of clozapine in this underrepresented population in clinical trials.Trial registrationClinicaltrials.gov: NCT04529226. EudraCT: 2020-000091-37

Efecto de los hábitats seminaturales del olivar sobre la biología de la familia Chrysopidae (Insecta:Neuroptera)

Uno de los desafíos de la agricultura del siglo XXI es incrementar su sostenibilidad y reducir su dependencia de los insumos externos. La expansión e intensificación de la agricultura hasta este momento ha provocado una disminución de los hábitats naturales y la biodiversidad, que ha derivado en la pérdida de servicios ecosistémicos de regulación y soporte como el control biológico de plagas. Todo ello ha llevado a la Unión Europea a promover la creación o protección de los hábitats seminaturales (HSNs), para mantener y restaurar la biodiversidad, así como proteger a los organismos beneficiosos importantes asociados. La familia Chrysopidae, con una amplia distribución en casi todos los ecosistemas agrícolas, forma parte del grupo de insectos beneficiosos del cultivo del olivo, donde depredan sobre tres de las dieciocho plagas que inciden en la producción y pueden causar graves pérdidas al olivar, especialmente la polilla del olivo, Prays oleae (Bernad, 1788) (Lepidoptera: Yponomeutidae). En este contexto, la conservación e incremento de las poblaciones de crisópidos en el olivar podría mejorar la presión natural sobre las plagas y reducir su dependencia de insumos externos. Los conocimientos adquiridos en esta tesis han permitido abordar aspectos de la biología de la familia Chrysopidae en el estrato arbóreo de los HSNs adyacentes al olivar. Este es un prerrequisito crucial para la elaboración de efectivos programas de manejo del hábitat orientados a la conservación de este valioso depredador.Tesis Univ. Granada

A Fuzzy Association Rule-Based Classification Model for High-Dimensional Problems with Genetic Rule Selection and Lateral Tuning

The inductive learning of fuzzy rule based classification systems suffers from exponential growth of the fuzzy rule search space when the number of patterns and/or variables becomes high. This growth makes the learning process more difficult and, in most cases, it leads to problems of scalability (in terms of the time and memory consumed) and/or complexity (with respect to the number of rules obtained and the number of variables included in each rule). In this work, we propose a fuzzy association rule-based classification method for high-dimensional problems based on three stages to obtain an accurate and compact fuzzy rule based classifier with a low computational cost. This method limits the order of the associations in the association rule extraction and considers the use of subgroup discovery based on an Improved Weighted Relative Accuracy measure to preselect the most interesting rules before a genetic post-processing process for rule selection and parameter tuning. The results obtained over twenty-six real-world datasets of different sizes and with different numbers of variables demonstrate the effectiveness of the proposed approach