Decomposition of a Multiobjective Optimization Problem Into a Number of Simple Multiobjective Subproblems

This letter suggests an approach for decomposing a multiobjective optimization problem (MOP) into a set of simple multiobjective optimization subproblems. Using this approach, it proposes MOEA/D-M2M, a new version of multiobjective optimization evolutionary algorithm-based decomposition. This proposed algorithm solves these subproblems in a collaborative way. Each subproblem has its own population and receives computational effort at each generation. In such a way, population diversity can be maintained, which is critical for solving some MOPs. Experimental studies have been conducted to compare MOEA/D-M2M with classic MOEA/D and NSGA-II. This letter argues that population diversity is more important than convergence in multiobjective evolutionary algorithms for dealing with some MOPs. It also explains why MOEA/D-M2M performs better. © 2013 IEEE

Sequencing and Genetic Variation of Multidrug Resistance Plasmids in Klebsiella pneumoniae

BACKGROUND: The development of multidrug resistance is a major problem in the treatment of pathogenic microorganisms by distinct antimicrobial agents. Characterizing the genetic variation among plasmids from different bacterial species or strains is a key step towards understanding the mechanism of virulence and their evolution. RESULTS: We applied a deep sequencing approach to 206 clinical strains of Klebsiella pneumoniae collected from 2002 to 2008 to understand the genetic variation of multidrug resistance plasmids, and to reveal the dynamic change of drug resistance over time. First, we sequenced three plasmids (70 Kb, 94 Kb, and 147 Kb) from a clonal strain of K. pneumoniae using Sanger sequencing. Using the Illumina sequencing technology, we obtained more than 17 million of short reads from two pooled plasmid samples. We mapped these short reads to the three reference plasmid sequences, and identified a large number of single nucleotide polymorphisms (SNPs) in these pooled plasmids. Many of these SNPs are present in drug-resistance genes. We also found that a significant fraction of short reads could not be mapped to the reference sequences, indicating a high degree of genetic variation among the collection of K. pneumoniae isolates. Moreover, we identified that plasmid conjugative transfer genes and antibiotic resistance genes are more likely to suffer from positive selection, as indicated by the elevated rates of nonsynonymous substitution. CONCLUSION: These data represent the first large-scale study of genetic variation in multidrug resistance plasmids and provide insight into the mechanisms of plasmid diversification and the genetic basis of antibiotic resistance

Compendium of 5810 genomes of sheep and goat gut microbiomes provides new insights into the glycan and mucin utilization

Background: Ruminant gut microbiota are critical in ecological adaptation, evolution, and nutrition utilization because it regulates energy metabolism, promotes nutrient absorption, and improves immune function. To study the functional roles of key gut microbiota in sheep and goats, it is essential to construct reference microbial gene catalogs and high-quality microbial genomes database. Results A total of 320 fecal samples were collected from 21 different sheep and goat breeds, originating from 32 distinct farms. Metagenomic deep sequencing and binning assembly were utilized to construct a comprehensive microbial genome information database for the gut microbiota. We successfully generated the largest reference gene catalogs for gut microbiota in sheep and goats, containing over 162 million and 82 million nonredundant predicted genes, respectively, with 49 million shared nonredundant predicted genes and 1138 shared species. We found that the rearing environment has a greater impact on microbial composition and function than the host’s species effect. Through subsequent assembly, we obtained 5810 medium- and high-quality metagenome-assembled genomes (MAGs), out of which 2661 were yet unidentified species. Among these MAGs, we identified 91 bacterial taxa that specifically colonize the sheep gut, which encode polysaccharide utilization loci for glycan and mucin degradation. Conclusions By shedding light on the co-symbiotic microbial communities in the gut of small ruminants, our study significantly enhances the understanding of their nutrient degradation and disease susceptibility. Our findings emphasize the vast potential of untapped resources in functional bacterial species within ruminants, further expanding our knowledge of how the ruminant gut microbiota recognizes and processes glycan and mucins

Abordagem da história da ciência na construção de um terrário, numa perspetiva de educação para o desenvolvimento sustentável

Mestrado em Ensino de Biologia e Geologia no 3º Ciclo do Ensino Básico e no Ensino SecundárioEm Portugal, avanços têm-se feito notar no que toca à tecnologia, o que leva a que novas aptidões e competências sejam desenvolvidas pelos cidadãos de forma a adaptarem-se à Era da informação. Para tal, é necessário que os alunos saiam já bem preparados das escolas de modo a que as suas aprendizagens atendam a essas mudanças, pois o ensino também implica mudança, evolução e crescimento, não só por parte dos estudantes mas também dos professores, das escolas e de todos os órgãos associados. Desta forma, vários métodos poderão ser implementados nas salas de aulas e um deles é a abordagem à História da Ciência. O presente trabalho investigativo procurou conhecer quais as aprendizagens, comportamentos e atitudes que os alunos desenvolveram ao longo das aulas, dando a conhecer os contributos que a construção de um terrário, através da História da Ciência, pode levar à educação de cidadãos informados, numa perspetiva de Educação para o Desenvolvimento Sustentável. A abordagem foi aplicada a alunos do 8.º ano, na disciplina de Ciências Naturais, utilizando várias técnicas e instrumentos de recolha de dados, nomeadamente, a observação, a análise documental e questionário. O recurso à construção e utilização de um material didático-pedagógico e a abordagem à História da Ciência, permitiram cativar o interesse dos alunos e centraliza-los no processo de ensino e de aprendizagem, no qual o aluno tem o principal papel. Dessa forma, foi possível averiguar como se contextualizam as aprendizagens através da abordagem utilizada, recolher e descrever as perspetivas dos alunos e em desenvolver as aprendizagens, comportamentos e atitudes, numa perspetiva de Educação para o Desenvolvimento Sustentável.In Portugal, advances have been made when it comes to Technology, which leads to new skills and competences to be developed by citizens in order to adapt to the Information age. To this end, it is necessary that students need to be well prepared when they conclude their studies, so that their acquired knowledge could meet these changes, for the teaching also implies changes, evolution and growth, not only by students but also by teachers, schools and all the associated teaching groups. This way, various methods can be implemented in the classroom and one of them is the approach to the History of Science. This research work was aimed to know which learnings, behaviors and attitudes that students developed during the lessons, so that it could be possible to publish the contribution of the construction of a terrarium, based in the History of Science, leading to the education of informed citizens, in a perspective of an Education for Sustainable Development. The approach was applied to 8th grade students, in the discipline of Natural Sciences, using various techniques and data collection instruments, like observation, documental analysis and a questionnaire. Building and using didactic-pedagogic material and applying History of Science knowledge, allowed to captivate the students' interest and it helped centralizing them in the process of teaching and learning, in which the student has the main role. Thus, it was possible to find out how to contextualize the learning through the used approaches, to collect and describe the perspectives of the students and developing the learning subject, behaviors and attitudes on a perspective of Education for the Sustainable Development

3D Copper Foam-Supported CuCo2O4 Nanosheet Arrays as Electrode for Enhanced Non-Enzymatic Glucose Sensing

CuCo2O4 anchored on Cu foam (CuCo2O4/CF) with polycrystalline features was fabricated by a mild process based on solvothermal reaction and subsequent calcination in this work. The structure and morphology of the obtained materials were thoroughly characterized by X-ray diffraction, X-ray photoelectron spectroscopy, field-emission scanning electron microscopy, and transmission electron microscopy. According to the above analysis, the morphology of the CuCo2O4 was nanosheet arrays. Meanwhile, the CuCo2O4 was grown on Cu foam successfully. The CuCo2O4/CF displayed good electrochemical properties for glucose detection at a linear range from 0 mM to 1.0 mM. Meanwhile, the detection limit was as low as 1 μM (S/N = 3), and the sensitivity was 20,981 μA·mM−1·cm−2. Moreover, the selectivity and the stability were tested with excellent results. This nanomaterial could show great potential application in electrochemical sensors

Energy-efficient access point clustering and power allocation in cell-free massive MIMO networks: a hierarchical deep reinforcement learning approach

Abstract Cell-free massive multiple-input multiple-output (CF-mMIMO) has attracted considerable attention due to its potential for delivering high data rates and energy efficiency (EE). In this paper, we investigate the resource allocation of downlink in CF-mMIMO systems. A hierarchical depth deterministic strategy gradient (H-DDPG) framework is proposed to jointly optimize the access point (AP) clustering and power allocation. The framework uses two-layer control networks operating on different timescales to enhance EE of downlinks in CF-mMIMO systems by cooperatively optimizing AP clustering and power allocation. In this framework, the high-level processing of system-level problems, namely AP clustering, enhances the wireless network configuration by utilizing DDPG on the large timescale while meeting the minimum spectral efficiency (SE) constraints for each user. The low layer solves the link-level sub-problem, that is, power allocation, and reduces interference between APs and improves transmission performance by utilizing DDPG on a small timescale while meeting the maximum transmit power constraint of each AP. Two corresponding DDPG agents are trained separately, allowing them to learn from the environment and gradually improve their policies to maximize the system EE. Numerical results validate the effectiveness of the proposed algorithm in term of its convergence speed, SE, and EE