121 resultados para Uniformly Convex


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Two transgenic callus lines of rice, stably expressing a β-glucuronidase (GUS) gene, were supertransformed with a set of constructs designed to silence the resident GUS gene. An inverted-repeat (i/r) GUS construct, designed to produce mRNA with self-complementarity, was much more effective than simple sense and antisense constructs at inducing silencing. Supertransforming rice calluses with a direct-repeat (d/r) construct, although not as effective as those with the i/r construct, was also substantially more effective in silencing the resident GUS gene than the simple sense and antisense constructs. DNA hybridisation analyses revealed that every callus line supertransformed with either simple sense or antisense constructs, and subsequently showing GUS silencing, had the silence-inducing transgenes integrated into the plant genome in inverted-repeat configurations. The silenced lines containing i/r and d/r constructs did not necessarily have inverted-repeat T-DNA insertions. There was significant methylation of the GUS sequences in most of the silenced lines but not in the unsilenced lines. However, demethylation treatment of silenced lines with 5-azacytidine did not reverse the post-transcriptional gene silencing (PTGS) of GUS. Whereas the levels of RNA specific to the resident GUS gene were uniformly low in the silenced lines, RNA specific to the inducer transgenes accumulated to a substantial level, and the majority of the i/r RNA was unpolyadenylated. Altogether, these results suggest that both sense- and antisense-mediated gene suppression share a similar molecular basis, that unpolyadenylated RNA plays an important role in PTGS, and that methylation is not essential for PTGS.

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BACKGROUND Inconsistencies in research findings on the impact of the built environment on walking across the life course may be methodologically driven. Commonly used methods to define 'neighbourhood', from which built environment variables are measured, may not accurately represent the spatial extent to which the behaviour in question occurs. This paper aims to provide new methods for spatially defining 'neighbourhood' based on how people use their surrounding environment. RESULTS Informed by Global Positioning Systems (GPS) tracking data, several alternative neighbourhood delineation techniques were examined (i.e., variable width, convex hull and standard deviation buffers). Compared with traditionally used buffers (i.e., circular and polygon network), differences were found in built environment characteristics within the newly created 'neighbourhoods'. Model fit statistics indicated that exposure measures derived from alternative buffering techniques provided a better fit when examining the relationship between land-use and walking for transport or leisure. CONCLUSIONS This research identifies how changes in the spatial extent from which built environment measures are derived may influence walking behaviour. Buffer size and orientation influences the relationship between built environment measures and walking for leisure in older adults. The use of GPS data proved suitable for re-examining operational definitions of neighbourhood.

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Many cell types form clumps or aggregates when cultured in vitro through a variety of mechanisms including rapid cell proliferation, chemotaxis, or direct cell-to-cell contact. In this paper we develop an agent-based model to explore the formation of aggregates in cultures where cells are initially distributed uniformly, at random, on a two-dimensional substrate. Our model includes unbiased random cell motion, together with two mechanisms which can produce cell aggregates: (i) rapid cell proliferation, and (ii) a biased cell motility mechanism where cells can sense other cells within a finite range, and will tend to move towards areas with higher numbers of cells. We then introduce a pair-correlation function which allows us to quantify aspects of the spatial patterns produced by our agent-based model. In particular, these pair-correlation functions are able to detect differences between domains populated uniformly at random (i.e. at the exclusion complete spatial randomness (ECSR) state) and those where the proliferation and biased motion rules have been employed - even when such differences are not obvious to the naked eye. The pair-correlation function can also detect the emergence of a characteristic inter-aggregate distance which occurs when the biased motion mechanism is dominant, and is not observed when cell proliferation is the main mechanism of aggregate formation. This suggests that applying the pair-correlation function to experimental images of cell aggregates may provide information about the mechanism associated with observed aggregates. As a proof of concept, we perform such analysis for images of cancer cell aggregates, which are known to be associated with rapid proliferation. The results of our analysis are consistent with the predictions of the proliferation-based simulations, which supports the potential usefulness of pair correlation functions for providing insight into the mechanisms of aggregate formation.

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Background Prevention strategies are critical to reduce infection rates in total joint arthroplasty (TJA), but evidence-based consensus guidelines on prevention of surgical site infection (SSI) remain heterogeneous and do not necessarily represent this particular patient population. Questions/Purposes What infection prevention measures are recommended by consensus evidence-based guidelines for prevention of periprosthetic joint infection? How do these recommendations compare to expert consensus on infection prevention strategies from orthopedic surgeons from the largest international tertiary referral centers for TJA? Patients and Methods A review of consensus guidelines was undertaken as described by Merollini et al. Four clinical guidelines met inclusion criteria: Centers for Disease Control and Prevention's, British Orthopedic Association, National Institute of Clinical Excellence's, and National Health and Medical Research Council's (NHMRC). Twenty-eight recommendations from these guidelines were used to create an evidence-based survey of infection prevention strategies that was administered to 28 orthopedic surgeons from members of the International Society of Orthopedic Centers. The results between existing consensus guidelines and expert opinion were then compared. Results Recommended strategies in the guidelines such as prophylactic antibiotics, preoperative skin preparation of patients and staff, and sterile surgical attire were considered critically or significantly important by the surveyed surgeons. Additional strategies such as ultraclean air/laminar flow, antibiotic cement, wound irrigation, and preoperative blood glucose control were also considered highly important by surveyed surgeons, but were not recommended or not uniformly addressed in existing guidelines on SSI prevention. Conclusion Current evidence-based guidelines are incomplete and evidence should be updated specifically to address patient needs undergoing TJA.

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We study the natural problem of secure n-party computation (in the computationally unbounded attack model) of circuits over an arbitrary finite non-Abelian group (G,⋅), which we call G-circuits. Besides its intrinsic interest, this problem is also motivating by a completeness result of Barrington, stating that such protocols can be applied for general secure computation of arbitrary functions. For flexibility, we are interested in protocols which only require black-box access to the group G (i.e. the only computations performed by players in the protocol are a group operation, a group inverse, or sampling a uniformly random group element). Our investigations focus on the passive adversarial model, where up to t of the n participating parties are corrupted.

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We describe a new species of dasyurid marsupial within the genus Antechinus that was previously known as a northern outlier of Dusky Antechinus (A. swainsonii). The Black-tailed Antechinus, Antechinus arktos sp. nov., is known only from areas of high altitude and high rainfall on the Tweed Volcano caldera of far south-east Queensland and north-east New South Wales, Australia. Antechinus arktos formerly sheltered under the taxonomic umbrella of A. swainsonii mimetes, the widespread mainland form of Dusky Antechinus. With the benefit of genetic hindsight, some striking morphological differences are herein resolved: A. s. mimetes is more uniformly deep brown-black to grizzled grey-brown from head to rump, with brownish (clove brown—raw umber) hair on the upper surface of the hindfoot and tail, whereas A. arktos is more vibrantly coloured, with a marked change from greyish-brown head to orange-brown rump, fuscous black on the upper surface of the hindfoot and dense, short fur on the evenly black tail. Further, A. arktos has marked orange-brown fur on the upper and lower eyelid, cheek and in front of the ear and very long guard hairs all over the body; these characters are more subtle in A. s. mimetes. There are striking genetic differences between the two species: at mtDNA, A. s. mimetes from north-east New South Wales is 10% divergent to A. arktos from its type locality at Springbrook NP, Queensland. In contrast, the Ebor A. s. mimetes clades closely with conspecifics from ACT and Victoria. A. arktos skulls are strikingly different to all subspecies of A. swainsonii. A. arktos are markedly larger than A. s. mimetes and A. s. swainsonii (Tasmania) for a range of craniodental measures. Antechinus arktos were historically found at a few proximate mountainous sites in south-east Queensland, and have only recently been recorded from or near the type locality. Even there, the species is likely in low abundance. The Black-tailed Antechinus has plausibly been detrimentally affected by climate change in recent decades, and will be at further risk with increasing warming trends.

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Rapidly increasing electricity demands and capacity shortage of transmission and distribution facilities are the main driving forces for the growth of Distributed Generation (DG) integration in power grids. One of the reasons for choosing a DG is its ability to support voltage in a distribution system. Selection of effective DG characteristics and DG parameters is a significant concern of distribution system planners to obtain maximum potential benefits from the DG unit. This paper addresses the issue of improving the network voltage profile in distribution systems by installing a DG of the most suitable size, at a suitable location. An analytical approach is developed based on algebraic equations for uniformly distributed loads to determine the optimal operation, size and location of the DG in order to achieve required levels of network voltage. The developed method is simple to use for conceptual design and analysis of distribution system expansion with a DG and suitable for a quick estimation of DG parameters (such as optimal operating angle, size and location of a DG system) in a radial network. A practical network is used to verify the proposed technique and test results are presented.

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Phase behavior of CO2 confined in porous fractal silica with volume fraction of SiO2 φs = 0.15 was investigated using small-angle neutron scattering (SANS) and ultrasmall-angle neutron scattering (USANS) techniques. The range of fluid densities (0<(FCO2)bulk<0.977 g/cm3) and temperatures (T=22 °C, 35 and 60 °C) corresponded to gaseous, liquid, near critical and supercritical conditions of the bulk fluid. The results revealed formation of a dense adsorbed phase in small pores with sizes D<40 A° at all temperatures. At low pressure (P <55 bar, (FCO2)bulk <0.2 g/cm3) the average fluid density in pores may exceed the density of bulk fluid by a factor up to 6.5 at T=22 °C. This “enrichment factor” gradually decreases with temperature, however significant fluid densification in small pores still exists at temperature T=60°C, i.e., far above the liquid-gas critical temperature of bulk CO2 (TC=31.1 °C). Larger pores are only partially filled with liquid-like adsorbed layer which coexists with unadsorbed fluid in the pore core. With increasing pressure, all pores become uniformly filled with the fluid, showing no measurable enrichment or depletion of the porous matrix with CO2.

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A key derivation function (KDF) is a function that transforms secret non-uniformly random source material together with some public strings into one or more cryptographic keys. These cryptographic keys are used with a cryptographic algorithm for protecting electronic data during both transmission over insecure channels and storage. In this thesis, we propose a new method for constructing a generic stream cipher based key derivation function. We show that our proposed key derivation function based on stream ciphers is secure if the under-lying stream cipher is secure. We simulate instances of this stream cipher based key derivation function using three eStream nalist: Trivium, Sosemanuk and Rabbit. The simulation results show these stream cipher based key derivation functions offer efficiency advantages over the more commonly used key derivation functions based on block ciphers and hash functions.

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Doping as one of the popular methods to manipulate the properties of nanomaterials has received extensive application in deriving different types of graphene derivates, while the understanding of the resonance properties of dopant graphene is still lacking in literature. Based on the large-scale molecular dynamics simulation, reactive empirical bond order potential, as well as the tersoff potential, the resonance properties of N-doped graphene were studied. The studied samples were established according to previous experiments with the N atom’s percentage ranging from 0.43%-2.98%, including three types of N dopant locations, i.e., graphitic N, pyrrolic N and pyridinic N. It is found that different percentages of N-dopant exert different influence to the resonance properties of the graphene, while the amount of N-dopant is not the only factor that determines its impact. For all the considered cases, a relative large percentage of N-dopant (2.98% graphitic N-dopant) is observed to introduce significant influence to the profile of the external energy, and thus lead to an extremely low Q-factor comparing with that of the pristine graphene. The most striking finding is that, the natural frequency of the defective graphene with N-dopant appears uniformly larger than that of the pristine defective graphene. While for the perfect graphene, the N-dopant shows less influence to its natural frequency. This study will enrich the current understanding of the influence of dopants on graphene, which will eventually shed lights on the design of different molecules-doped graphene sheet.

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This paper presents a novel place recognition algorithm inspired by the recent discovery of overlapping and multi-scale spatial maps in the rodent brain. We mimic this hierarchical framework by training arrays of Support Vector Machines to recognize places at multiple spatial scales. Place match hypotheses are then cross-validated across all spatial scales, a process which combines the spatial specificity of the finest spatial map with the consensus provided by broader mapping scales. Experiments on three real-world datasets including a large robotics benchmark demonstrate that mapping over multiple scales uniformly improves place recognition performance over a single scale approach without sacrificing localization accuracy. We present analysis that illustrates how matching over multiple scales leads to better place recognition performance and discuss several promising areas for future investigation.

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In this paper we introduce a new technique to obtain the slow-motion dynamics in nonequilibrium and singularly perturbed problems characterized by multiple scales. Our method is based on a straightforward asymptotic reduction of the order of the governing differential equation and leads to amplitude equations that describe the slowly-varying envelope variation of a uniformly valid asymptotic expansion. This may constitute a simpler and in certain cases a more general approach toward the derivation of asymptotic expansions, compared to other mainstream methods such as the method of Multiple Scales or Matched Asymptotic expansions because of its relation with the Renormalization Group. We illustrate our method with a number of singularly perturbed problems for ordinary and partial differential equations and recover certain results from the literature as special cases. © 2010 - IOS Press and the authors. All rights reserved.

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We have developed a technique that circumvents the process of elimination of secular terms and reproduces the uniformly valid approximations, amplitude equations, and first integrals. The technique is based on a rearrangement of secular terms and their grouping into the secular series that multiplies the constants of the asymptotic expansion. We illustrate the technique by deriving amplitude equations for standard nonlinear oscillator and boundary-layer problems. © 2008 The American Physical Society.

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Plasmas, the 4th state of matter, uniformly transform natural precursors with different chemical composition in solid, liquid, and gas states into the same functional vertical graphenes in a single-step process within a few minutes. Functional vertical graphenes show reliable biosensing properties, strong binding with proteins, and improved adhesion to substrates.

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In this study, we improve the insulation performance of polymeric nano-dielectrics by using plasma pre-treatment on the filled nanoparticles. Non-equilibrium atmospheric-pressure plasma is employed to modify a commercial type of silane-coated SiO2 nanoparticles. The treated nanoparticles and the synthesized epoxy-based nanocomposites are characterized using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS). The plasma-treated SiO2 nanoparticles can disperse uniformly and form strong covalent bonds with the molecules of the polymer matrix. Moreover, the electrical insulation properties of the synthesized nanocomposites are investigated. Results show that the nanocomposites with plasma-treated SiO2 nanoparticles obtain improved dielectric breakdown strength and extended endurance under intense electrical ageing process.