180 resultados para Insect sounds.


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Background: Developing sampling strategies to target biological pests such as insects in stored grain is inherently difficult owing to species biology and behavioural characteristics. The design of robust sampling programmes should be based on an underlying statistical distribution that is sufficiently flexible to capture variations in the spatial distribution of the target species. Results: Comparisons are made of the accuracy of four probability-of-detection sampling models - the negative binomial model,1 the Poisson model,1 the double logarithmic model2 and the compound model3 - for detection of insects over a broad range of insect densities. Although the double log and negative binomial models performed well under specific conditions, it is shown that, of the four models examined, the compound model performed the best over a broad range of insect spatial distributions and densities. In particular, this model predicted well the number of samples required when insect density was high and clumped within experimental storages. Conclusions: This paper reinforces the need for effective sampling programs designed to detect insects over a broad range of spatial distributions. The compound model is robust over a broad range of insect densities and leads to substantial improvement in detection probabilities within highly variable systems such as grain storage.

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RNA interference induced in insects after ingestion of plant-expressed hairpin RNA offers promise for managing devastating crop pests

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These wordless songs were composed as music first, and soundtrack second. There is a difference. A soundtrack will always be connected with whatever it is accompanying. Music doesn’t neccessarily need to reference anything else. The Empty City transformed a picture book into a non-verbal performance combining the live and animated. Without spoken words the show would dance on the dangerous intersection of music, image and action. In both theatre and film (and this production drew on both traditions) soundtrack and music are often added on at the end when everything’s been pre-determined, a passive, responsive mode for such a powerful artform. It’s literally added in ‘post’. In The Empty City, music was present from its inception and grew with the show. It was active in process and product. It frequently led rehearsals and shaped other key decisions in virtual and live performance. Rather than tailor-make music towards pre-determined moments, independent compositions created without specific reference to narrative experimented with the creation of a flock of small musical pieces. I was interested in seeing how they flew and where they roosted, rather than having them born and raised in (narrative) captivity. The sonic palette is largely acoustic, incorporating ukulele, prepared piano and supported by a range of other elements tending towards electronica. Eventually more than seventy pieces of music were made for this show, twice the number used. These pieces were then placed in relation to the emerging scenes, then adapted in duration, texture and progression to develop a relationship with the scene. In this way, music (even when it’s synced) has a conversation with a performance, an exchange that may result in surprise rather than fulfillment of expectation. Leitmotif emerged from loops and layers, as the pieces of music ‘conversed’ with each other, rather than being premeditated and imposed. Nineteen of these tracks are compiled for this release, which finds the compositions (which progressed through many versions) poised at the moment between their fullest iteration as ‘music’ and their editing and full incorporation into a sychronised soundtrack. They are released as the began: as 'music-alone' (Kivy) In picture-book writing, the mutual interplay of text and image is sometimes referred to as interanimation , and this is the kind of symbiosis this project sought in the creation of the soundtrack. Reviewers of the noted the important role of the soundtrack in two separate productions of The Empty City: “The original score…takes centre stage” (Borhani, 2013) “…swept up in its repetition of sounds and images, like a Bach fugue” (Zampatti, 2013)

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The mitochondrial (mt) genome is, to date, the most extensively studied genomic system in insects, outnumbering nuclear genomes tenfold and representing all orders versus very few. Phylogenomic analysis methods have been tested extensively, identifying compositional bias and rate variation, both within and between lineages, as the principal issues confronting accurate analyses. Major studies at both inter- and intraordinal levels have contributed to our understanding of phylogenetic relationships within many groups. Genome rearrangements are an additional data type for defining relationships, with rearrangement synapomorphies identified across multiple orders and at many different taxonomic levels. Hymenoptera and Psocodea have greatly elevated rates of rearrangement offering both opportunities and pitfalls for identifying rearrangement synapomorphies in each group. Finally, insects are model systems for studying aberrant mt genomes, including truncated tRNAs and multichromosomal genomes. Greater integration of nuclear and mt genomic studies is necessary to further our understanding of insect genomic evolution.

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Motivated by the analysis of the Australian Grain Insect Resistance Database (AGIRD), we develop a Bayesian hurdle modelling approach to assess trends in strong resistance of stored grain insects to phosphine over time. The binary response variable from AGIRD indicating presence or absence of strong resistance is characterized by a majority of absence observations and the hurdle model is a two step approach that is useful when analyzing such a binary response dataset. The proposed hurdle model utilizes Bayesian classification trees to firstly identify covariates and covariate levels pertaining to possible presence or absence of strong resistance. Secondly, generalized additive models (GAMs) with spike and slab priors for variable selection are fitted to the subset of the dataset identified from the Bayesian classification tree indicating possibility of presence of strong resistance. From the GAM we assess trends, biosecurity issues and site specific variables influencing the presence of strong resistance using a variable selection approach. The proposed Bayesian hurdle model is compared to its frequentist counterpart, and also to a naive Bayesian approach which fits a GAM to the entire dataset. The Bayesian hurdle model has the benefit of providing a set of good trees for use in the first step and appears to provide enough flexibility to represent the influence of variables on strong resistance compared to the frequentist model, but also captures the subtle changes in the trend that are missed by the frequentist and naive Bayesian models.

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Over the past decade the mitochondrial (mt) genome has become the most widely used genomic resource available for systematic entomology. While the availability of other types of ‘–omics’ data – in particular transcriptomes – is increasing rapidly, mt genomes are still vastly cheaper to sequence and are far less demanding of high quality templates. Furthermore, almost all other ‘–omics’ approaches also sequence the mt genome, and so it can form a bridge between legacy and contemporary datasets. Mitochondrial genomes have now been sequenced for all insect orders, and in many instances representatives of each major lineage within orders (suborders, series or superfamilies depending on the group). They have also been applied to systematic questions at all taxonomic scales from resolving interordinal relationships (e.g. Cameron et al., 2009; Wan et al., 2012; Wang et al., 2012), through many intraordinal (e.g. Dowton et al., 2009; Timmermans et al., 2010; Zhao et al. 2013a) and family-level studies (e.g. Nelson et al., 2012; Zhao et al., 2013b) to population/biogeographic studies (e.g. Ma et al., 2012). Methodological issues around the use of mt genomes in insect phylogenetic analyses and the empirical results found to date have recently been reviewed by Cameron (2014), yet the technical aspects of sequencing and annotating mt genomes were not covered. Most papers which generate new mt genome report their methods in a simplified form which can be difficult to replicate without specific knowledge of the field. Published studies utilize a sufficiently wide range of approaches, usually without justification for the one chosen, that confusion about commonly used jargon such as ‘long PCR’ and ‘primer walking’ could be a serious barrier to entry. Furthermore, sequenced mt genomes have been annotated (gene locations defined) to wildly varying standards and improving data quality through consistent annotation procedures will benefit all downstream users of these datasets. The aims of this review are therefore to: 1. Describe in detail the various sequencing methods used on insect mt genomes; 2. Explore the strengths/weakness of different approaches; 3. Outline the procedures and software used for insect mt genome annotation, and; 4. Highlight quality control steps used for new annotations, and to improve the re-annotation of previously sequenced mt genomes used in systematic or comparative research.

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Semantic knowledge is supported by a widely distributed neuronal network, with differential patterns of activation depending upon experimental stimulus or task demands. Despite a wide body of knowledge on semantic object processing from the visual modality, the response of this semantic network to environmental sounds remains relatively unknown. Here, we used fMRI to investigate how access to different conceptual attributes from environmental sound input modulates this semantic network. Using a range of living and manmade sounds, we scanned participants whilst they carried out an object attribute verification task. Specifically, we tested visual perceptual, encyclopedic, and categorical attributes about living and manmade objects relative to a high-level auditory perceptual baseline to investigate the differential patterns of response to these contrasting types of object-related attributes, whilst keeping stimulus input constant across conditions. Within the bilateral distributed network engaged for processing environmental sounds across all conditions, we report here a highly significant dissociation within the left hemisphere between the processing of visual perceptual and encyclopedic attributes of objects.

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To identify and categorize complex stimuli such as familiar objects or speech, the human brain integrates information that is abstracted at multiple levels from its sensory inputs. Using cross-modal priming for spoken words and sounds, this functional magnetic resonance imaging study identified 3 distinct classes of visuoauditory incongruency effects: visuoauditory incongruency effects were selective for 1) spoken words in the left superior temporal sulcus (STS), 2) environmental sounds in the left angular gyrus (AG), and 3) both words and sounds in the lateral and medial prefrontal cortices (IFS/mPFC). From a cognitive perspective, these incongruency effects suggest that prior visual information influences the neural processes underlying speech and sound recognition at multiple levels, with the STS being involved in phonological, AG in semantic, and mPFC/IFS in higher conceptual processing. In terms of neural mechanisms, effective connectivity analyses (dynamic causal modeling) suggest that these incongruency effects may emerge via greater bottom-up effects from early auditory regions to intermediate multisensory integration areas (i.e., STS and AG). This is consistent with a predictive coding perspective on hierarchical Bayesian inference in the cortex where the domain of the prediction error (phonological vs. semantic) determines its regional expression (middle temporal gyrus/STS vs. AG/intraparietal sulcus).

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A travel article about Nova Scotia, and the area's annual Celtic music festival. I ARRIVED in Cape Breton on the occasion of the Fibre Festival, run not only by the South Haven Guild of Weavers but also the Baddeck Quilters Guild. And yet I might not have noticed that it was on, had it not been for a car, shrouded entirely by a quilt cover, that was parked outside the Volunteer Fire Department Hall. I was on my way to the Alexander Graham Bell Museum a little further along Baddeck's main street. But I stopped, for who wouldn't stop to look at the various fibres of Cape Breton. The hall had been divided between weavers and quilters. Naturally, I left hoping that one day this ancient divide might be healed...

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Weta possess typical Ensifera ears. Each ear comprises three functional parts: two equally sized tympanal membranes, an underlying system of modified tracheal chambers, and the auditory sensory organ, the crista acustica. This organ sits within an enclosed fluid-filled channel-previously presumed to be hemolymph. The role this channel plays in insect hearing is unknown. We discovered that the fluid within the channel is not actually hemolymph, but a medium composed principally of lipid from a new class. Three-dimensional imaging of this lipid channel revealed a previously undescribed tissue structure within the channel, which we refer to as the olivarius organ. Investigations into the function of the olivarius reveal de novo lipid synthesis indicating that it is producing these lipids in situ from acetate. The auditory role of this lipid channel was investigated using Laser Doppler vibrometry of the tympanal membrane, which shows that the displacement of the membrane is significantly increased when the lipid is removed from the auditory system. Neural sensitivity of the system, however, decreased upon removal of the lipid-a surprising result considering that in a typical auditory system both the mechanical and auditory sensitivity are positively correlated. These two results coupled with 3D modelling of the auditory system lead us to hypothesize a model for weta audition, relying strongly on the presence of the lipid channel. This is the first instance of lipids being associated with an auditory system outside of the Odentocete cetaceans, demonstrating convergence for the use of lipids in hearing.

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Opsins are ancient molecules that enable animal vision by coupling to a vitamin-derived chromophore to form lightsensitive photopigments. The primary drivers of evolutionary diversification in opsins are thought to be visual tasks related to spectral sensitivity and color vision. Typically, only a few opsin amino acid sites affect photopigment spectral sensitivity. We show that opsin genes of the North American butterfly Limenitis arthemis have diversified along a latitudinal cline, consistent with natural selection due to environmental factors. We sequenced single nucleotide(SNP) polymorphisms in the coding regions of the ultraviolet (UVRh), blue (BRh), and long-wavelength (LWRh) opsin genes from ten butterfly populations along the eastern United States and found that a majority of opsin SNPs showed significant clinal variation. Outlier detection and analysis of molecular variance indicated that many SNPs are under balancing selection and show significant population structure. This contrasts with what we found by analysing SNPs in the wingless and EF-1 alpha loci, and from neutral amplified fragment length polymorphisms, which show no evidence of significant locus-specific or genome-wide structure among populations. Using a combination of functional genetic and physiological approaches, including expression in cell culture, transgenic Drosophila, UV-visible spectroscopy, and optophysiology, we show that key BRh opsin SNPs that vary clinally have almost no effect on spectral sensitivity. Our results suggest that opsin diversification in this butterfly is more consistent with natural selection unrelated to spectral tuning. Some of the clinally varying SNPs may instead play a role in regulating opsin gene expression levels or the thermostability of the opsin protein. Lastly, we discuss the possibility that insect opsins might have important, yet-to-be elucidated, adaptive functions in mediating animal responses to abiotic factors, such as temperature or photoperiod.

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Limited data on cervical auscultation (CA) sounds in normal swallows of various food and fluid textures during the transitional feeding period of 4-36 months exists. This study documents the acoustic and perceptual parameters of swallowing sounds in healthy children aged 4–36 months over a range of food and fluid consistencies.

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Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising technology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of the approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labeling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means. The outcome of this approach is a soft K-means algorithm similar to the EM algorithm for Gaussian mixture models. The results show the algorithm delivers decision boundaries that consistently classify the field into three clusters, one for each crop health level. The methodology presented in this paper represents a venue for further research towards automated crop damage assessments and biosecurity surveillance.