142 research outputs found

    Prospects for local co-governance

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    British local authorities and their partners are increasingly developing new ways of working together with local communities. The nature of this co-working, however, is complex, multi-faceted and little understood. This article argues for greater clarity of thinking on the topic, by analysing this co-working as a form of political co-governance, and drawing attention in particular to issues of scale and democracy. Using evidence from a study of 43 local authority areas, 16 authorities are identified where co-governance is practised, following three main types of approach: service-influencing, service-delivering and parish council developing. It is concluded that strengthening political co-governance is essential for a healthy democracy

    Deep reinforcement learning for drone navigation using sensor data

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    Mobile robots such as unmanned aerial vehicles (drones) can be used for surveillance, monitoring and data collection in buildings, infrastructure and environments. The importance of accurate and multifaceted monitoring is well known to identify problems early and prevent them escalating. This motivates the need for flexible, autonomous and powerful decision-making mobile robots. These systems need to be able to learn through fusing data from multiple sources. Until very recently, they have been task specific. In this paper, we describe a generic navigation algorithm that uses data from sensors on-board the drone to guide the drone to the site of the problem. In hazardous and safety-critical situations, locating problems accurately and rapidly is vital. We use the proximal policy optimisation deep reinforcement learning algorithm coupled with incremental curriculum learning and long short-term memory neural networks to implement our generic and adaptable navigation algorithm. We evaluate different configurations against a heuristic technique to demonstrate its accuracy and efficiency. Finally, we consider how safety of the drone could be assured by assessing how safely the drone would perform using our navigation algorithm in real-world scenarios

    Tomato: a crop species amenable to improvement by cellular and molecular methods

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    Tomato is a crop plant with a relatively small DNA content per haploid genome and a well developed genetics. Plant regeneration from explants and protoplasts is feasable which led to the development of efficient transformation procedures. In view of the current data, the isolation of useful mutants at the cellular level probably will be of limited value in the genetic improvement of tomato. Protoplast fusion may lead to novel combinations of organelle and nuclear DNA (cybrids), whereas this technique also provides a means of introducing genetic information from alien species into tomato. Important developments have come from molecular approaches. Following the construction of an RFLP map, these RFLP markers can be used in tomato to tag quantitative traits bred in from related species. Both RFLP's and transposons are in the process of being used to clone desired genes for which no gene products are known. Cloned genes can be introduced and potentially improve specific properties of tomato especially those controlled by single genes. Recent results suggest that, in principle, phenotypic mutants can be created for cloned and characterized genes and will prove their value in further improving the cultivated tomato.

    Overexpression of the aphid-induced serine protease inhibitor <i>CI2c </i>gene in barley affects the generalist green peach aphid, not the specialist bird cherry-oat aphid

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    <div><p>Aphids are serious pests in crop plants. In an effort to identify plant genes controlling resistance against aphids, we have here studied a protease inhibitor, CI2c in barley (<i>Hordeum vulgare</i> L.). The <i>CI2c</i> gene was earlier shown to be upregulated by herbivory of the bird cherry-oat aphid <i>(Rhopalosiphum padi</i> L.<i>)</i> in barley genotypes with moderate resistance against this aphid, but not in susceptible lines. We hypothesized that CI2c contributes to the resistance. To test this idea, cDNA encoding <i>CI2c</i> was overexpressed in barley and bioassays were carried out with <i>R</i>. <i>padi</i>. For comparison, tests were carried out with the green peach aphid (<i>Myzus persicae</i> Sulzer), for which barley is a poor host. The performance of <i>R</i>. <i>padi</i> was not different on the <i>CI2c</i>-overexpressing lines in comparison to controls in test monitoring behavior and fecundity. <i>M</i>. <i>persicae</i> preference was affected as shown in the choice test, this species moved away from control plants, but remained on the <i>CI2c</i>-overexpressing lines. <i>R</i>. <i>padi</i>-induced responses related to defense were repressed in the overexpressing lines as compared to in control plants or the moderately resistant genotypes. A putative susceptibility gene, coding for a β-1,3-glucanase was more strongly induced by aphids in one of the <i>CI2c</i>-overexpressing lines. The results indicate that the CI2c inhibitor in overexpressing lines affects aphid-induced responses by suppressing defense. This is of little consequence to the specialist <i>R</i>.<i>padi</i>, but causes lower non-host resistance towards the generalist <i>M</i>. <i>persicae</i> in barley.</p></div

    Carbon Nanotubes in Tissue Engineering

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    For their peculiar features carbon nanotubes (CNTs) are emerging in many areas of nanotechnology applications. CNT-based technology has been increasingly proposed for biomedical applications, to develop biomolecule nanocarriers, bionanosensors and smart material for tissue engineering purposes. In the following chapter this latter application will be explored, describing why CNTs can be considered an ideal material able to support and boost the growth and the proliferation of many kind of tissues

    Defining the Functional Domain of Programmed Cell Death 10 through Its Interactions with Phosphatidylinositol-3,4,5-Trisphosphate

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    Cerebral cavernous malformations (CCM) are vascular abnormalities of the central nervous system predisposing blood vessels to leakage, leading to hemorrhagic stroke. Three genes, Krit1 (CCM1), OSM (CCM2), and PDCD10 (CCM3) are involved in CCM development. PDCD10 binds specifically to PtdIns(3,4,5)P3 and OSM. Using threading analysis and multi-template modeling, we constructed a three-dimensional model of PDCD10. PDCD10 appears to be a six-helical-bundle protein formed by two heptad-repeat-hairpin structures (α1–3 and α4–6) sharing the closest 3D homology with the bacterial phosphate transporter, PhoU. We identified a stretch of five lysines forming an amphipathic helix, a potential PtdIns(3,4,5)P3 binding site, in the α5 helix. We generated a recombinant wild-type (WT) and three PDCD10 mutants that have two (Δ2KA), three (Δ3KA), and five (Δ5KA) K to A mutations. Δ2KA and Δ3KA mutants hypothetically lack binding residues to PtdIns(3,4,5)P3 at the beginning and the end of predicted helix, while Δ5KA completely lacks all predicted binding residues. The WT, Δ2KA, and Δ3KA mutants maintain their binding to PtdIns(3,4,5)P3. Only the Δ5KA abolishes binding to PtdIns(3,4,5)P3. Both Δ5KA and WT show similar secondary and tertiary structures; however, Δ5KA does not bind to OSM. When WT and Δ5KA are co-expressed with membrane-bound constitutively-active PI3 kinase (p110-CAAX), the majority of the WT is co-localized with p110-CAAX at the plasma membrane where PtdIns(3,4,5)P3 is presumably abundant. In contrast, the Δ5KA remains in the cytoplasm and is not present in the plasma membrane. Combining computational modeling and biological data, we propose that the CCM protein complex functions in the PI3K signaling pathway through the interaction between PDCD10 and PtdIns(3,4,5)P3
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