Waste on the roadside, 'poi-sute' waste: Its distribution and elution potential of pollutants into environment

ArticleWASTE MANAGEMENT. 29(3):1192-1197 (2009)journal articl

Complex sequencing rules of birdsong can be explained by simple hidden Markov processes

Complex sequencing rules observed in birdsongs provide an opportunity to investigate the neural mechanism for generating complex sequential behaviors. To relate the findings from studying birdsongs to other sequential behaviors, it is crucial to characterize the statistical properties of the sequencing rules in birdsongs. However, the properties of the sequencing rules in birdsongs have not yet been fully addressed. In this study, we investigate the statistical propertiesof the complex birdsong of the Bengalese finch (Lonchura striata var. domestica). Based on manual-annotated syllable sequences, we first show that there are significant higher-order context dependencies in Bengalese finch songs, that is, which syllable appears next depends on more than one previous syllable. This property is shared with other complex sequential behaviors. We then analyze acoustic features of the song and show that higher-order context dependencies can be explained using first-order hidden state transition dynamics with redundant hidden states. This model corresponds to hidden Markov models (HMMs), well known statistical models with a large range of application for time series modeling. The song annotation with these models with first-order hidden state dynamics agreed well with manual annotation, the score was comparable to that of a second-order HMM, and surpassed the zeroth-order model (the Gaussian mixture model (GMM)), which does not use context information. Our results imply that the hierarchical representation with hidden state dynamics may underlie the neural implementation for generating complex sequences with higher-order dependencies

Topoisomer Differentiation of Molecular Knots by FTICR MS: Lessons from Class II Lasso Peptides

Lasso peptides constitute a class of bioactive peptides sharing a knotted structure where the C-terminal tail of the peptide is threaded through and trapped within an N-terminalmacrolactamring. The structural characterization of lasso structures and differentiation from their unthreaded topoisomers is not trivial and generally requires the use of complementary biochemical and spectroscopic methods. Here we investigated two antimicrobial peptides belonging to the class II lasso peptide family and their corresponding unthreaded topoisomers: microcin J25 (MccJ25), which is known to yield two-peptide product ions specific of the lasso structure under collisioninduced dissociation (CID), and capistruin, for which CID does not permit to unambiguously assign the lasso structure. The two pairs of topoisomers were analyzed by electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI-FTICR MS) upon CID, infrared multiple photon dissociation (IRMPD), and electron capture dissociation (ECD). CID and ECDspectra clearly permitted to differentiate MccJ25 from its non-lasso topoisomer MccJ25-Icm, while for capistruin, only ECD was informative and showed different extent of hydrogen migration (formation of c\bullet/z from c/z\bullet) for the threaded and unthreaded topoisomers. The ECD spectra of the triply-charged MccJ25 and MccJ25-lcm showed a series of radical b-type product ions {\eth}b0In{\TH}. We proposed that these ions are specific of cyclic-branched peptides and result from a dual c/z\bullet and y/b dissociation, in the ring and in the tail, respectively. This work shows the potentiality of ECD for structural characterization of peptide topoisomers, as well as the effect of conformation on hydrogen migration subsequent to electron capture

A compact statistical model of the song syntax in Bengalese finch

Songs of many songbird species consist of variable sequences of a finite number of syllables. A common approach for characterizing the syntax of these complex syllable sequences is to use transition probabilities between the syllables. This is equivalent to the Markov model, in which each syllable is associated with one state, and the transition probabilities between the states do not depend on the state transition history. Here we analyze the song syntax in a Bengalese finch. We show that the Markov model fails to capture the statistical properties of the syllable sequences. Instead, a state transition model that accurately describes the statistics of the syllable sequences includes adaptation of the self-transition probabilities when states are repeatedly revisited, and allows associations of more than one state to the same syllable. Such a model does not increase the model complexity significantly. Mathematically, the model is a partially observable Markov model with adaptation (POMMA). The success of the POMMA supports the branching chain network hypothesis of how syntax is controlled within the premotor song nucleus HVC, and suggests that adaptation and many-to-one mapping from neural substrates to syllables are important features of the neural control of complex song syntax

A robust system for RNA interference in the chicken using a modified microRNA operon

AbstractRNA interference (RNAi) provides an effective method to silence gene expression and investigate gene function. However, RNAi tools for the chicken embryo have largely been adapted from vectors designed for mammalian cells. Here we present plasmid and retroviral RNAi vectors specifically designed for optimal gene silencing in chicken cells. The vectors use a chicken U6 promoter to express RNAs modelled on microRNA30, which are embedded within chicken microRNA operon sequences to ensure optimal Drosha and Dicer processing of transcripts. The chicken U6 promoter works significantly better than promoters of mammalian origin and in combination with a microRNA operon expression cassette (MOEC), achieves up to 90% silencing of target genes. By using a MOEC, we show that it is also possible to simultaneously silence two genes with a single vector. The vectors express either RFP or GFP markers, allowing simple in vivo tracking of vector delivery. Using these plasmids, we demonstrate effective silencing of Pax3, Pax6, Nkx2.1, Nkx2.2, Notch1 and Shh in discrete regions of the chicken embryonic nervous system. The efficiency and ease of use of this RNAi system paves the way for large-scale genetic screens in the chicken embryo