142 research outputs found

    Lectins and Their Roles in Pests Control

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    The structure of gene-gene networks beyond pairwise interactions

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    Despite its high and direct impact on nearly all biological processes, the underlying structure of gene-gene interaction networks is investigated so far according to pair connections. To address this, we explore the gene interaction networks of the yeast Saccharomyces cerevisiae beyond pairwise interaction using the structural balance theory (SBT). Specifically, we ask whether essential and nonessential gene interaction networks are structurally balanced. We study triadic interactions in the weighted signed undirected gene networks and observe that balanced and unbalanced triads are over and underrepresented in both networks, thus beautifully in line with the strong notion of balance. Moreover, we note that the energy distribution of triads is significantly different in both essential and nonessential networks compared with the shuffled networks. Yet, this difference is greater in the essential network regarding the frequency as well as the energy of triads. Additionally, results demonstrate that triads in the essential gene network are more interconnected through sharing common links, while in the nonessential network they tend to be isolated. Last but not least, we investigate the contribution of all-length signed walks and its impact on the degree of balance. Our findings reveal that interestingly when considering longer cycles the nonessential gene network is more balanced compared to the essential network.Comment: 16 pages, 5 figures, 4 table

    Simple method for the characterization of intense Laguerre-Gauss vector vortex beams

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    We report on a method for the characterization of intense, structured optical fields through the analysis of the size and surface structures formed inside the annular ablation crater created on the target surface. In particular, we apply the technique to laser ablation of crystalline silicon induced by femtosecond vector vortex beams. We show that a rapid direct estimate of the beam waist parameter is obtained through a measure of the crater radii. The variation of the internal and external radii of the annular crater as a function of the laser pulse energy, at fixed number of pulses, provides another way to evaluate the beam spot size through numerical fitting of the obtained experimental data points. A reliable estimate of the spot size is of paramount importance to investigate pulsed laser-induced effects on the target material. Our experimental findings offer a facile way to characterize focused, high intensity complex optical vector beams which are more and more applied in laser-matter interaction experiments

    Facial grimace testing as an assay of neuropathic pain-related behavior in a mouse model of cervical spinal cord injury.

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    A major portion of individuals affected by traumatic spinal cord injury (SCI) experience one or more types of chronic neuropathic pain (NP), which is often intractable to currently available treatments. The availability of reliable behavioral assays in pre-clinical models of SCI-induced NP is therefore critical to assess the efficacy of new potential therapies. Commonly used assays to evaluate NP-related behavior in rodents, such as Hargreaves thermal and von Frey mechanical testing, rely on the withdrawal response to an evoked stimulus. However, other assays that test spontaneous/non-evoked NP-related behavior or supraspinal aspects of NP would be highly useful for a more comprehensive assessment of NP following SCI. The Mouse Grimace Scale (MGS) is a tool to assess spontaneous, supraspinal pain-like behaviors in mice; however, the assay has not been characterized in a mouse model of SCI-induced chronic NP, despite the critical importance of mouse genetics as an experimental tool. We found that beginning 2 weeks after cervical contusion, SCI mice exhibited increased facial grimace features compared to laminectomy-only control mice, and this grimace phenotype persisted to the chronic time point of 5 weeks post-injury. We also found a significant relationship between facial grimace score and the evoked forepaw withdrawal response in both the Hargreaves and von Frey tests at 5 weeks post-injury when both laminectomy-only and SCI mice were included in the analysis. However, within only the SCI group, there was no correlation between grimace score and Hargreaves or von Frey responses. These results indicate both that facial grimace analysis can be used as an assay of spontaneous NP-related behavior in the mouse model of SCI and that the information provided by the MGS may be different than that provided by evoked tests of sensory function

    Secondary electron yield reduction by femtosecond pulse laser-induced periodic surface structuring

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    The electron-cloud phenomenon is one cause of beam instabilities in high intensity positive particle accelerators. Among the proposed techniques to mitigate or control this detrimental effect, micro-/nano-geometrical modifications of vacuum chamber surfaces are promising to reduce the number of emitted secondary electrons. Femtosecond laser surface structuring readily allows the fabrication of Laser Induced Periodic Surface Structures (LIPSS) and is utilized in several fields, but has not yet been tested for secondary electron emission reduction. In this study, such treatment is carried out on copper samples using linearly and circularly polarized femtosecond laser pulses. The influence of the formed surface textures on the secondary electron yield (SEY) is studied. We investigate the morphological properties as well as the chemical composition by means of SEM, AFM, Raman and XPS analyses. Surface modification with linearly polarized light is more effective than using circularly polarized light, leading to a significant SEY reduction. Even though the SEY maximum is only reduced to a value of ~1.7 compared to standard laser-induced surface roughening approaches, the femtosecond-LIPSS process enables to limit material ablation as well as the production of undesired dust, and drastically reduces the number of redeposited nanoparticles at the surface, which are detrimental for applications in particle accelerators. Moreover, conditioning tests reveal that LIPSS processed Cu can reach SEY values below unity at electron irradiation doses above 10−3 C/mm2

    Learning Interpretable Rules for Multi-label Classification

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    Multi-label classification (MLC) is a supervised learning problem in which, contrary to standard multiclass classification, an instance can be associated with several class labels simultaneously. In this chapter, we advocate a rule-based approach to multi-label classification. Rule learning algorithms are often employed when one is not only interested in accurate predictions, but also requires an interpretable theory that can be understood, analyzed, and qualitatively evaluated by domain experts. Ideally, by revealing patterns and regularities contained in the data, a rule-based theory yields new insights in the application domain. Recently, several authors have started to investigate how rule-based models can be used for modeling multi-label data. Discussing this task in detail, we highlight some of the problems that make rule learning considerably more challenging for MLC than for conventional classification. While mainly focusing on our own previous work, we also provide a short overview of related work in this area.Comment: Preprint version. To appear in: Explainable and Interpretable Models in Computer Vision and Machine Learning. The Springer Series on Challenges in Machine Learning. Springer (2018). See http://www.ke.tu-darmstadt.de/bibtex/publications/show/3077 for further informatio
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