Validation of microsatellite markers for cytotype discrimination in the model grass Brachypodium distachyon

Brachypodium distachyon (2n = 2x = 10) is a small annual grass species where the existence of three different cytotypes (10, 20 and 30 chromosomes) has long been regarded as a case of autopolyploid series, with x = 5. However, it has been demonstrated that the cytotypes assumed to be polyploids represent two separate Brachypodium species recently named as B. stacei (2n = 2x = 20) and B. hybridum (2n = 4x = 30). The aim of this study was to find a PCR-based alternative approach that could replace standard cytotyping methods (i. e., chromosome counting and flow cytometry) to characterize each of the three Brachypodium species. We have analyzed with four microsatellite (SSR) markers eighty-three Brachypodium distachyon-type lines from varied locations in Spain, including the Balearic and Canary Islands. Within this set of lines, 64, 4 and 15 had 10, 20 and 30 chromosomes, respectively. The surveyed markers produced cytotype-specific SSR profiles. So, a single amplification product was generated in the diploid samples, with non-overlapping allelic ranges between the 2n = 10 and 2n = 20 cytotypes, whereas two bands, one in the size range of each of the diploid cytotypes, were amplified in the 2n = 30 lines. Furthermore, the remarkable size difference obtained with the SSR ALB165 allowed the identification of the Brachypodium species by simple agarose gel electrophoresis

A Methodology to Engineer and Validate Dynamic Multi-level Multi-agent Based Simulations

This article proposes a methodology to model and simulate complex systems, based on IRM4MLS, a generic agent-based meta-model able to deal with multi-level systems. This methodology permits the engineering of dynamic multi-level agent-based models, to represent complex systems over several scales and domains of interest. Its goal is to simulate a phenomenon using dynamically the lightest representation to save computer resources without loss of information. This methodology is based on two mechanisms: (1) the activation or deactivation of agents representing different domain parts of the same phenomenon and (2) the aggregation or disaggregation of agents representing the same phenomenon at different scales.Comment: Presented at 3th International Workshop on Multi-Agent Based Simulation, Valencia, Spain, 5th June 201

The disconnect between knowledge and perceptions: A study of fishermen’s local ecological knowledge and their perception of the state of fisheries and how these are managed in the Dominican Republic

Understanding what fishers know about the ecology of the fish they catch, and how they perceive the state and management of their fisheries can guide efforts towards more sustainable fishing practices. We tested relationships between fishers’ local ecological knowledge (LEK) and their perceptions of their fisheries and of marine protected areas in the Dominican Republic. A qualitative-quantitative methodological sequence using data from interviews with 152 multi-species fishers revealed variable, but generally high levels of LEK, particularly of habitat use and predator–prey interactions. The majority reported negative perceptions of the state of their fishery and were aware of local management actions. Contrary to study expectations, we found that fishers’ LEK, measured by Cultural Consensus Analysis, did not significantly co-vary with their perceptions of the state of fisheries or with their awareness of, and support for, marine protected areas. These results highlight the need to identify and understand barriers to information flow and communication in local fisheries’ social/political networks

Optimization of multichip RFID tag antenna with genetic algorithm and method of moments

A specific procedure is implemented for the optimization of passive part of multichip RFID tag antenna, based on the performance parameter in terms of newly developed concepts. Examples are given and significant improvements have been observed comparing with previous results, which verifies the approach

Severity classification in cases of Collagen VI-related myopathy with Convolutional Neural Networks and handcrafted texture features

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Magnetic Resonance Imaging (MRI) is a non-invasive tool for the clinical assessment of low-prevalence neuromuscular disorders. Automated diagnosis methods might reduce the need for biopsies and provide valuable information on disease follow-up. In this paper, three methods are proposed to classify target muscles in Collagen VI-related myopathy cases, based on their degree of involvement, notably a Convolutional Neural Network, a Fully Connected Network to classify texture features, and a hybrid method combining the two feature sets. The proposed methods were evaluated on axial T1-weighted Turbo Spin-Echo MRI from 26 subjects, including Ullrich Congenital Muscular Dystrophy and Bethlem Myopathy patients at different evolution stages. The hybrid model achieved the best cross-validation results, with a global accuracy of 93.8%, and F-scores of 0.99, 0.82, and 0.95, for healthy, mild and moderate/severe cases, respectively.info:eu-repo/semantics/acceptedVersio

Severity classification in cases of Collagen VI-related myopathy with Convolutional Neural Networks and handcrafted texture features

(C) 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Magnetic Resonance Imaging (MRI) is a non-invasive tool for the clinical assessment of low-prevalence neuromuscular disorders. Automated diagnosis methods might reduce the need for biopsies and provide valuable information on disease follow-up. In this paper, three methods are proposed to classify target muscles in Collagen VI-related myopathy cases, based on their degree of involvement, notably a Convolutional Neural Network, a Fully Connected Network to classify texture features, and a hybrid method combining the two feature sets. The proposed methods were evaluated on axial T1-weighted Turbo Spin-Echo MRI from 26 subjects, including Ullrich Congenital Muscular Dystrophy and Bethlem Myopathy patients at different evolution stages. The hybrid model achieved the best cross-validation results, with a global accuracy of 93.8%, and F-scores of 0.99, 0.82, and 0.95, for healthy, mild and moderate/severe cases, respectively.info:eu-repo/semantics/acceptedVersio

Decentralized control for urban drainage systems via population dynamics: Bogotá case study

Trabajo presentado a la European Control Conference celebrada en Linz (Alemania) del 15 al 17 de julio de 2015.Control of Urban Drainage Systems (UDS) is studied for cases in which the distribution of run–off through the channels of a system is inefficient, i.e. when the capacity of some structures is not used optimally. In this paper, a decentralized population-dynamics-based control for UDS is presented, particularly using the replicator and projection dynamics. For the design, a methodology to make a partitioning of the system is introduced, and the design of a population–dynamics–based control per each partition is proposed. Moreover, a stability analysis of the closed–loop system is made by using passivity theory. Finally, simulation results show the proposed approach performance in a segment of the Bogota stormwater UDS case study.COLCIENCIAS supports J. Barreiro-Gómez and G. Obando. Agència de Gestió d’Ajust Universitaris i de Recerca AGAUR supports J. Barreiro-Gómez. This work has been partially supported by the projects “Drenaje urbano y cambio climático: Hacia los sistemas de alcantarillados del futuro. Fase II. COLCIENCIAS 633/2013”, ECOCIS (Ref. DPI2013-48243-C2-1-R), and EFFINET (Ref. FP7-ICT-2011-8-31855).Peer Reviewe

Biotrickling filter modeling for styrene abatement. Part 2: Simulating a two-phase partitioning bioreactor

Peer ReviewedPostprint (author's final draft