5,306 research outputs found

    Learning recurrent representations for hierarchical behavior modeling

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    We propose a framework for detecting action patterns from motion sequences and modeling the sensory-motor relationship of animals, using a generative recurrent neural network. The network has a discriminative part (classifying actions) and a generative part (predicting motion), whose recurrent cells are laterally connected, allowing higher levels of the network to represent high level phenomena. We test our framework on two types of data, fruit fly behavior and online handwriting. Our results show that 1) taking advantage of unlabeled sequences, by predicting future motion, significantly improves action detection performance when training labels are scarce, 2) the network learns to represent high level phenomena such as writer identity and fly gender, without supervision, and 3) simulated motion trajectories, generated by treating motion prediction as input to the network, look realistic and may be used to qualitatively evaluate whether the model has learnt generative control rules

    Multi-resolution Tensor Learning for Large-Scale Spatial Data

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    High-dimensional tensor models are notoriously computationally expensive to train. We present a meta-learning algorithm, MMT, that can significantly speed up the process for spatial tensor models. MMT leverages the property that spatial data can be viewed at multiple resolutions, which are related by coarsening and finegraining from one resolution to another. Using this property, MMT learns a tensor model by starting from a coarse resolution and iteratively increasing the model complexity. In order to not "over-train" on coarse resolution models, we investigate an information-theoretic fine-graining criterion to decide when to transition into higher-resolution models. We provide both theoretical and empirical evidence for the advantages of this approach. When applied to two real-world large-scale spatial datasets for basketball player and animal behavior modeling, our approach demonstrate 3 key benefits: 1) it efficiently captures higher-order interactions (i.e., tensor latent factors), 2) it is orders of magnitude faster than fixed resolution learning and scales to very fine-grained spatial resolutions, and 3) it reliably yields accurate and interpretable models

    MODULATING MALE AGGRESSION AND COURTSHIP: DETECTING EXTERNAL PHEROMONAL AND NUTRITIONAL INFORMATION

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    Survival and reproduction in the natural world requires an organism to identify and react to the presence of environmental stimuli in a time and cue dependent manner. Such temporal specificity requires the development and use of specialized sensory organs that receive this external sensory information. Neurons within the specialized sensory organs respond to touch, taste, pheromones, chemicals, and light, and transduce this information to the central brain. In many systems, gustatory and olfactory chemosensation in particular, provides critical information regarding sex and species identification as well as the status of food resources. The output of neurons which receive chemical information is regulated by the action of biogenic amines, including serotonin, dopamine, and norepinephrine. In this dissertation I examined the role of octopamine (the invertebrate structural homologue of norepinephrine) signaling in the regulation of two behaviors required for survival and reproduction; aggression and courtship. In chapter II, I, along with my colleagues, demonstrate that neurons bearing the taste receptor Gr32a form putative synapses with octopamine neurons within the subesophageal zone, and that octopamine neurons promote male aggression and courtship behavior. These findings help to explain how an organism selects appropriate behavioral responses when confronted with the pheromonal signals of a rival male. In chapter III, I examined the effects of octopamine signaling on taste sensitization. In this section, I examined the distribution and function of neurons that express the Oaβ1R receptor, and found that these neurons are sugar sensitive. As the presence of a food source is known to be a major contributor to the generation of aggressive and courtship behavior, these findings imply a mechanism by which exposure to an environmental stimulus or changes in internal octopamine signaling may sensitize a particular form of sensory input

    Cultural diffusion in humans and other animals

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    This is the author's post print version of an article published in definitive form in Current Opinion in Psychology, Volume 8, April 2016, Pages 15–21.The definitive published version is available from: doi:10.1016/j.copsyc.2015.09.002Available online 14 September 2015Copyright © 2015 Elsevier Ltd.Recent years have seen an enormous expansion and progress in studies of the cultural diffusion processes through which behaviour patterns, ideas and artifacts are transmitted within and between generations of humans and other animals. The first of two main approaches focuses on identifying, tracing and understanding cultural diffusion as it naturally occurs, an essential foundation to any science of culture. This endeavor has been enriched in recent years by sophisticated statistical methods and surprising new discoveries particularly in humans, other primates and cetaceans. This work has been complemented by a growing corpus of powerful, purpose-designed cultural diffusion experiments with captive and natural populations that have facilitated the rigorous identification and analysis of cultural diffusion in species from insects to humans.John Templeton Foundatio

    Developing European conservation and mitigation tools for pollination services: approaches of the STEP (Status and Trends of European Pollinators) project

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    Pollinating insects form a key component of European biodiversity, and provide a vital ecosystem service to crops and wild plants. There is growing evidence of declines in both wild and domesticated pollinators, and parallel declines in plants relying upon them. The STEP project (Status and Trends of European Pollinators, 2010-2015, www.stepproject.net) is documenting critical elements in the nature and extent of these declines, examining key functional traits associated with pollination deficits, and developing a Red List for some European pollinator groups. Together these activities are laying the groundwork for future pollinator monitoring programmes. STEP is also assessing the relative importance of potential drivers of pollinator declines, including climate change, habitat loss and fragmentation, agrochemicals, pathogens, alien species, light pollution, and their interactions. We are measuring the ecological and economic impacts of declining pollinator services and floral resources, including effects on wild plant populations, crop production and human nutrition. STEP is reviewing existing and potential mitigation options, and providing novel tests of their effectiveness across Europe. Our work is building upon existing and newly developed datasets and models, complemented by spatially-replicated campaigns of field research to fill gaps in current knowledge. Findings are being integrated into a policy-relevant framework to create evidence-based decision support tools. STEP is establishing communication links to a wide range of stakeholders across Europe and beyond, including policy makers, beekeepers, farmers, academics and the general public. Taken together, the STEP research programme aims to improve our understanding of the nature, causes, consequences and potential mitigation of declines in pollination services at local, national, continental and global scales

    Pest risk analysis for Bactrocera invadens : Guidelines on Pest Risk Analysis

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    Stripping related moisture damage has been recognized as one of the major pavement distresses since the early 1990s. The main objective of this study is to establish an effective test protocol to quantify moisture susceptibility of asphalt pavements. To this end, selective test methods (Texas Boiling test, Tensile Strength Ratio, Retained Stability, and Hamburg Wheel Test), and procedures based on surface chemistries and molecular-level mechanistic properties have been investigated in this study. Firstly, a comprehensive list of literature related to moisture damage in asphalts was reviewed. Based on the literature review, a detailed project plan and test matrix were developed. Binder samples originated from two different crude sources were collected. The moisture resistance related tests such as static contact angle measurements and Texas Boiling tests were conducted. Besides, asphalt binders’ nanomechanical properties using an Atomic Force Microscopy (AFM) and surface chemistries using a static contact were evaluated in the laboratory. Based on limited test data and analysis, it is concluded that there does not exist any single test method that all agencies are comfortable and equipped to follow in their daily work as each technique has some merits and demerits. However, the Texas Boiling test is found to be the simplest method that requires minimal time and resources. On the other hand, surface chemistry and atomic force microscope-based techniques are becoming popular among researchers and pavement professionals. Findings of this study are expected to help ARDOT in selecting an appropriate moisture resistance test method that is simple, reliable, and easy to implement in their routine work
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