Level-Based Analysis of the Population-Based Incremental Learning Algorithm

The Population-Based Incremental Learning (PBIL) algorithm uses a convex combination of the current model and the empirical model to construct the next model, which is then sampled to generate offspring. The Univariate Marginal Distribution Algorithm (UMDA) is a special case of the PBIL, where the current model is ignored. Dang and Lehre (GECCO 2015) showed that UMDA can optimise LeadingOnes efficiently. The question still remained open if the PBIL performs equally well. Here, by applying the level-based theorem in addition to Dvoretzky--Kiefer--Wolfowitz inequality, we show that the PBIL optimises function LeadingOnes in expected time $\mathcal{O}(n\lambda \log \lambda + n^2)$ for a population size $\lambda = \Omega(\log n)$, which matches the bound of the UMDA. Finally, we show that the result carries over to BinVal, giving the fist runtime result for the PBIL on the BinVal problem.Comment: To appea

Identification of host genes potentially implicated in the Malus pumila and ‘Candidatus Phytoplasma mali’ interactions

Two‘Candidatus Phytoplasma mali’ strains (AP and AT), were studied in experimentally infected apple trees to analyze transcriptional profiles during interaction with phytoplasmas. Three groups of sample combinations were employed: healthy - infected, symptomatic - non-symptomatic, and AP-infected - AT-infected sample. The majority of genes were differently expressed between healthy and infected samples. Changes in gene expression involved a wide spectrum of biological functions, including processes of metabolism, cell defence, photosynthesis, transport, transcription, signal transduction and protein synthesis. The possible effect of phytoplasma infection on these processes and their relationships with disease development, symptom appearance and possible plant defence system is discussed. Keywords: Apple, phytoplasmas, ‘Ca. P. mali’, gene expression, transcriptom

Preliminary evaluation of antimicrobial activity of some chemicals on in vitro apple shoots infected by 'Candidatus Phytoplasma mali'.

peer reviewe

Low-rank multi-parametric covariance identification

We propose a differential geometric construction for families of low-rank covariance matrices, via interpolation on low-rank matrix manifolds. In contrast with standard parametric covariance classes, these families offer significant flexibility for problem-specific tailoring via the choice of "anchor" matrices for the interpolation. Moreover, their low-rank facilitates computational tractability in high dimensions and with limited data. We employ these covariance families for both interpolation and identification, where the latter problem comprises selecting the most representative member of the covariance family given a data set. In this setting, standard procedures such as maximum likelihood estimation are nontrivial because the covariance family is rank-deficient; we resolve this issue by casting the identification problem as distance minimization. We demonstrate the power of these differential geometric families for interpolation and identification in a practical application: wind field covariance approximation for unmanned aerial vehicle navigation

Exploring bacterial communities in aquaponic systems

Aquaponics is a production system based on the dynamic equilibrium between fish, plants, and microorganisms. In order to better understand the role of microorganisms in this tripartite relationship, we studied the bacterial communities hosted in eight aquaponic and aquaculture systems. The bacterial communities were analyzed by 16S rRNA gene deep sequencing. At the phylum level, the bacterial communities from all systems were relatively similar with a predominance of Proteobacteria and Bacteroidetes. At the genus level, however, the communities present in the sampled systems were more heterogeneous. The biofilter samples harbored more diverse communities than the corresponding sump samples. The core microbiomes from the coupled and decoupled systems shared more common operational taxonomic units than with the aquaculture systems. Eventually, some of the taxa identified in the systems could have beneficial functions for plant growth and health, but a deeper analysis would be required to identify the precise functions involved in aquaponics

Genome-wide DNA methylation changes in a mouse model of infection-mediated neurodevelopmental disorders

Background Prenatal exposure to infectious or inflammatory insults increases the risk of neurodevelopmental disorders. Using a well-established mouse model of prenatal viral-like immune activation, we examined whether this pathological association involves genome-wide DNA methylation differences at single nucleotide resolution. Methods Prenatal immune activation was induced by maternal treatment with the viral mimetic polyriboinosinic-polyribocytidylic acid in middle or late gestation. Following behavioral and cognitive characterization of the adult offspring (n = 12 per group), unbiased capture array bisulfite sequencing was combined with subsequent matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and quantitative real-time polymerase chain reaction analyses to quantify DNA methylation changes and transcriptional abnormalities in the medial prefrontal cortex of immune-challenged and control offspring. Gene ontology term enrichment analysis was used to explore shared functional pathways of genes with differential DNA methylation. Results Adult offspring of immune-challenged mothers displayed hyper- and hypomethylated CpGs at numerous loci and at distinct genomic regions, including genes relevant for gamma-aminobutyric acidergic differentiation and signaling (e.g., Dlx1, Lhx5, Lhx8), Wnt signaling (Wnt3, Wnt8a, Wnt7b), and neural development (e.g., Efnb3, Mid1, Nlgn1, Nrxn2). Altered DNA methylation was associated with transcriptional changes of the corresponding genes. The epigenetic and transcriptional effects were dependent on the offspring\u2019s age and were markedly influenced by the precise timing of prenatal immune activation. Conclusions Prenatal viral-like immune activation is capable of inducing stable DNA methylation changes in the medial prefrontal cortex. These long-term epigenetic modifications are a plausible mechanism underlying the disruption of prefrontal gene transcription and behavioral functions in subjects with prenatal infectious histories