960 resultados para Coarse Authentication


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The amygdala is consistently implicated in biologically relevant learning tasks such as Pavlovian conditioning. In humans, the ability to identify individual faces based on the social outcomes they have predicted in the past constitutes a critical form of associative learning that can be likened to “social conditioning.” To capture such learning in a laboratory setting, participants learned about faces that predicted negative, positive, or neutral social outcomes. Participants reported liking or disliking the faces in accordance with their learned social value. During acquisition, we observed differential functional magnetic resonance imaging activation across the human amygdaloid complex consistent with previous lesion, electrophysiological, and functional neuroimaging data. A region of the medial ventral amygdala and a region of the dorsal amygdala/substantia innominata showed signal increases to both Negative and Positive faces, whereas a lateral ventral region displayed a linear representation of the valence of faces such that Negative > Positive > Neutral. This lateral ventral locus also differed from the dorsal and medial loci in that the magnitude of these responses was more resistant to habituation. These findings document a role for the human amygdala in social learning and reveal coarse regional dissociations in amygdala activity that are consistent with previous human and nonhuman animal data.

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Preface. Iron is considered to be a minor element employed, in a variety of forms, by nearly all living organisms. In some cases, it is utilised in large quantities, for instance for the formation of magnetosomes within magnetotactic bacteria or during use of iron as a respiratory donor or acceptor by iron oxidising or reducing bacteria. However, in most cases the role of iron is restricted to its use as a cofactor or prosthetic group assisting the biological activity of many different types of protein. The key metabolic processes that are dependent on iron as a cofactor are numerous; they include respiration, light harvesting, nitrogen fixation, the Krebs cycle, redox stress resistance, amino acid synthesis and oxygen transport. Indeed, it is clear that Life in its current form would be impossible in the absence of iron. One of the main reasons for the reliance of Life upon this metal is the ability of iron to exist in multiple redox states, in particular the relatively stable ferrous (Fe2+) and ferric (Fe3+) forms. The availability of these stable oxidation states allows iron to engage in redox reactions over a wide range of midpoint potentials, depending on the coordination environment, making it an extremely adaptable mediator of electron exchange processes. Iron is also one of the most common elements within the Earth’s crust (5% abundance) and thus is considered to have been readily available when Life evolved on our early, anaerobic planet. However, as oxygen accumulated (the ‘Great oxidation event’) within the atmosphere some 2.4 billion years ago, and as the oceans became less acidic, the iron within primordial oceans was converted from its soluble reduced form to its weakly-soluble oxidised ferric form, which precipitated (~1.8 billion years ago) to form the ‘banded iron formations’ (BIFs) observed today in Precambrian sedimentary rocks around the world. These BIFs provide a geological record marking a transition point away from the ancient anaerobic world towards modern aerobic Earth. They also indicate a period over which the bio-availability of iron shifted from abundance to limitation, a condition that extends to the modern day. Thus, it is considered likely that the vast majority of extant organisms face the common problem of securing sufficient iron from their environment – a problem that Life on Earth has had to cope with for some 2 billion years. This struggle for iron is exemplified by the competition for this metal amongst co-habiting microorganisms who resort to stealing (pirating) each others iron supplies! The reliance of micro-organisms upon iron can be disadvantageous to them, and to our innate immune system it represents a chink in the microbial armour, offering an opportunity that can be exploited to ward off pathogenic invaders. In order to infect body tissues and cause disease, pathogens must secure all their iron from the host. To fight such infections, the host specifically withdraws available iron through the action of various iron depleting processes (e.g. the release of lactoferrin and lipocalin-2) – this represents an important strategy in our defence against disease. However, pathogens are frequently able to deploy iron acquisition systems that target host iron sources such as transferrin, lactoferrin and hemoproteins, and thus counteract the iron-withdrawal approaches of the host. Inactivation of such host-targeting iron-uptake systems often attenuates the pathogenicity of the invading microbe, illustrating the importance of ‘the battle for iron’ in the infection process. The role of iron sequestration systems in facilitating microbial infections has been a major driving force in research aimed at unravelling the complexities of microbial iron transport processes. But also, the intricacy of such systems offers a challenge that stimulates the curiosity. One such challenge is to understand how balanced levels of free iron within the cytosol are achieved in a way that avoids toxicity whilst providing sufficient levels for metabolic purposes – this is a requirement that all organisms have to meet. Although the systems involved in achieving this balance can be highly variable amongst different microorganisms, the overall strategy is common. On a coarse level, the homeostatic control of cellular iron is maintained through strict control of the uptake, storage and utilisation of available iron, and is co-ordinated by integrated iron-regulatory networks. However, much yet remains to be discovered concerning the fine details of these different iron regulatory processes. As already indicated, perhaps the most difficult task in maintaining iron homeostasis is simply the procurement of sufficient iron from external sources. The importance of this problem is demonstrated by the plethora of distinct iron transporters often found within a single bacterium, each targeting different forms (complex or redox state) of iron or a different environmental condition. Thus, microbes devote considerable cellular resource to securing iron from their surroundings, reflecting how successful acquisition of iron can be crucial in the competition for survival. The aim of this book is provide the reader with an overview of iron transport processes within a range of microorganisms and to provide an indication of how microbial iron levels are controlled. This aim is promoted through the inclusion of expert reviews on several well studied examples that illustrate the current state of play concerning our comprehension of how iron is translocated into the bacterial (or fungal) cell and how iron homeostasis is controlled within microbes. The first two chapters (1-2) consider the general properties of microbial iron-chelating compounds (known as ‘siderophores’), and the mechanisms used by bacteria to acquire haem and utilise it as an iron source. The following twelve chapters (3-14) focus on specific types of microorganism that are of key interest, covering both an array of pathogens for humans, animals and plants (e.g. species of Bordetella, Shigella, , Erwinia, Vibrio, Aeromonas, Francisella, Campylobacter and Staphylococci, and EHEC) as well as a number of prominent non-pathogens (e.g. the rhizobia, E. coli K-12, Bacteroides spp., cyanobacteria, Bacillus spp. and yeasts). The chapters relay the common themes in microbial iron uptake approaches (e.g. the use of siderophores, TonB-dependent transporters, and ABC transport systems), but also highlight many distinctions (such as use of different types iron regulator and the impact of the presence/absence of a cell wall) in the strategies employed. We hope that those both within and outside the field will find this book useful, stimulating and interesting. We intend that it will provide a source for reference that will assist relevant researchers and provide an entry point for those initiating their studies within this subject. Finally, it is important that we acknowledge and thank wholeheartedly the many contributors who have provided the 14 excellent chapters from which this book is composed. Without their considerable efforts, this book, and the understanding that it relays, would not have been possible. Simon C Andrews and Pierre Cornelis

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Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.

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Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.

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1. Estimates of seed bank depletion rates are essential for modelling and management of plant populations. The seed bag burial method is often used to measure seed mortality in the soil. However, the density of seeds within seed bags is higher than densities in natural seed banks, which may elevate levels of pathogens and influence seed mortality. The aim of this study was to quantify the effects of fungi and seed density within buried mesh bags on the mortality of seeds. Striga hermonthica was chosen as the study species because it has been widely studied but different methods for measuring seed mortality in the soil have yielded contradictory estimates. 2. Seed bags were buried in soil and exhumed at regular time intervals to monitor mortality of the seeds in three field experiments during two rainy seasons. The effect of fungal activity on seed mortality was evaluated in a fungi exclusion experiment. Differences in seed-to-seed interaction were obtained by using two and four densities within the seed bags in consecutive years. Densities were created by mixing 1000 seeds with 0, 10, 100 or 1000 g of coarse sand. 3. The mortality rate was significantly lower when fungi were excluded, indicating the possible role of pathogenic fungi. 4. Decreasing the density of seeds in bags significantly reduced seed mortality, most probably because of decreased seed-to-seed contamination by pathogenic fungi. 5. Synthesis and applications. Models of plant populations in general and annual weeds in particular often use values from the literature for seed bank depletion rates. These depletion rates have often been estimated by the seed bag burial method, yet seed density within seed bags may be unrealistically high. Consequently, estimates of seed mortality rates may be too high because of an overestimation of the effects of soil or seed-borne pathogens. Species that have been classified from such studies as having short-lived seed banks may need to be re-assessed using realistic densities either within seed bags or otherwise. Similarly, models of seed bank dynamics based on such overestimated depletion rates may lead to incorrect conclusions regarding the seed banks and, perhaps, the management of weeds and rare species.

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The influence of sedimentation, depth and substratum angle on sponge assemblages in the Wakatobi region, south-eastern Sulawesi, Indonesia was considered. Sponge assemblages were sampled from two reef localities. The first reef (Sampela) was highly impacted by high sedimentation rates with fine sediment particles that settle slowly, while the second (Hoga) experienced only fast settling coarse sediment with lower overall sedimentation rates. Sponge assemblages were sampled (area occupied and numbers) on the reef fiat (0 m) and at 5 (reef crest), 10 and 15 m (15 m at Hoga only). Some significant (P < 0.001) differences were observed in the area occupied and the number of sponge patches between surface angles and sites. Significantly lower (t > 4.61, df = 9, P < 0.001) sponge numbers, percentage cover and richness were associated with the reef flat at both sites compared with all other depths at each site, with the exception of abundance of sponges on the reef flat at Sampela, which was much greater than at any other depth sampled. Species richness increased with depth at both sites but differences between surface angles were only recorded at Sampela, with higher species richness being found on vertical, inclined and horizontal surfaces respectively A total of 100 sponge species (total area sampled 52.5 m(2)) was reported from the two sites, with 58 species found at Sampela and 71 species at Hoga (41% of species shared). Multi-dimensional scaling (MDS) indicated differences in assemblage structure between sites and most depth intervals, but not substratum angles. A number of biological (e.g. competition and predation) and physical (e.g. sedimentation and aerial exposure) factors were considered to control sponge abundance and richness. Unexpectedly a significant (F-1,F-169 = 148.98, P < 0.001) positive linear relationship was found between sponge density and area occupied. In areas of high sponge coverage, the number of patches was also high, possibly due to fragmentation of large sponges produced as a result of predation and physical disturbance. The MDS results were also the same whether sponge numbers or percentage cover estimates were used, suggesting that although these different approaches yield different sorts of information, the same assemblage structure can be identified.

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Inhibition is intimately involved in the ability to select a target for a goal-directed movement. The effect of distracters on the deviation of oculomotor trajectories and landing positions provides evidence of such inhibition. individual saccade trajectories and landing positions may deviate initially either towards, or away from, a competing distracter-the direction and extent of this deviation depends upon saccade latency and the target to distracter separation. However, the underlying commonality of the sources of oculomotor inhibition has not been investigated. Here we report the relationship between distracter-related deviation of saccade trajectory, landing position and saccade latency. Observers saccaded to a target which could be accompanied by a distracter shown at various distances from very close (10 angular degrees) to far away (120 angular degrees). A fixation-gap paradigm was used to manipulate latency independently of the influence of competing distracters. When distracters were close to the target, saccade trajectory and landing position deviated toward the distracter position, while at greater separations landing position was always accurate but trajectories deviated away from the distracters. Different spatial patterns of deviations across latency were found. This pattern of results is consistent with the metrics of the saccade reflecting coarse pooling of the ongoing activity at the distracter location: saccade trajectory reflects activity at saccade initiation while landing position reveals activity at saccade end. (C) 2009 Elsevier B.V. All rights reserved.

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The design space of emerging heterogenous multi-core architectures with re-configurability element makes it feasible to design mixed fine-grained and coarse-grained parallel architectures. This paper presents a hierarchical composite array design which extends the curret design space of regular array design by combining a sequence of transformations. This technique is applied to derive a new design of a pipelined parallel regular array with different dataflow between phases of computation.

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Every winter, the high-latitude oceans are struck by severe storms that are considerably smaller than the weather-dominating synoptic depressions1. Accompanied by strong winds and heavy precipitation, these often explosively developing mesoscale cyclones—termed polar lows1—constitute a threat to offshore activities such as shipping or oil and gas exploitation. Yet owing to their small scale, polar lows are poorly represented in the observational and global reanalysis data2 often used for climatological investigations of atmospheric features and cannot be assessed in coarse-resolution global simulations of possible future climates. Here we show that in a future anthropogenically warmed climate, the frequency of polar lows is projected to decline. We used a series of regional climate model simulations to downscale a set of global climate change scenarios3 from the Intergovernmental Panel of Climate Change. In this process, we first simulated the formation of polar low systems in the North Atlantic and then counted the individual cases. A previous study4 using NCEP/NCAR re-analysis data5 revealed that polar low frequency from 1948 to 2005 did not systematically change. Now, in projections for the end of the twenty-first century, we found a significantly lower number of polar lows and a northward shift of their mean genesis region in response to elevated atmospheric greenhouse gas concentration. This change can be related to changes in the North Atlantic sea surface temperature and mid-troposphere temperature; the latter is found to rise faster than the former so that the resulting stability is increased, hindering the formation or intensification of polar lows. Our results provide a rare example of a climate change effect in which a type of extreme weather is likely to decrease, rather than increase.

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Information on the distribution and behavior of C fractions in soil particle sizes is crucial for understanding C dynamics in soil. At present little is known about the behavior of the C associated with silt-size particles. We quantified the concentrations, distribution, and enrichment of total C (TC), readily oxidizable C (ROC), hotwater- extractable C (HWC), and cold-water-extractable C (CWC) fractions in coarse (63–20-mm), medium (20–6.3-mm), and fine (6.3–2-mm) silt-size subfractions and in coarse (2000–250 mm) and fine (250–63 mm) sand and clay (<2-mm) soil fractions isolated from bulk soil (<2 mm), and 2- to 4-mm aggregate-size fraction of surface (0–25 cm) and subsurface (25–55 cm) soils under different land uses. All measured C fractions varied significantly across all soil particle-size fractions. The highest C concentrations were associated with the <20-mm soil fractions and peaked in the medium (20–6.3-mm) and fine (6.3–2-mm) silt subfractions in most treatments. Carbon enrichment ratios (ERC) revealed the dual behavior of the C fractions associated with the medium silt-size fraction, demonstrating the simultaneous enrichment of TC and ROC, and the depletion of HWC and CWC fractions. The medium silt (20–6.3-mm) subfraction was identified in this study as a zone where the associated C fractions exhibit transitory qualities. Our results show that investigating subfractions within the silt-size particle fraction provides better understanding of the behavior of C fractions in this soil fraction.

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We present extensive molecular dynamics simulations of the dynamics of diluted long probe chains entangled with a matrix of shorter chains. The chain lengths of both components are above the entanglement strand length, and the ratio of their lengths is varied over a wide range to cover the crossover from the chain reptation regime to tube Rouse motion regime of the long probe chains. Reducing the matrix chain length results in a faster decay of the dynamic structure factor of the probe chains, in good agreement with recent neutron spin echo experiments. The diffusion of the long chains, measured by the mean square displacements of the monomers and the centers of mass of the chains, demonstrates a systematic speed-up relative to the pure reptation behavior expected for monodisperse melts of sufficiently long polymers. On the other hand, the diffusion of the matrix chains is only weakly perturbed by the diluted long probe chains. The simulation results are qualitatively consistent with the theoretical predictions based on constraint release Rouse model, but a detailed comparison reveals the existence of a broad distribution of the disentanglement rates, which is partly confirmed by an analysis of the packing and diffusion of the matrix chains in the tube region of the probe chains. A coarse-grained simulation model based on the tube Rouse motion model with incorporation of the probability distribution of the tube segment jump rates is developed and shows results qualitatively consistent with the fine scale molecular dynamics simulations. However, we observe a breakdown in the tube Rouse model when the short chain length is decreased to around N-S = 80, which is roughly 3.5 times the entanglement spacing N-e(P) = 23. The location of this transition may be sensitive to the chain bending potential used in our simulations.

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The NERC UK SOLAS-funded Reactive Halogens in the Marine Boundary Layer (RHaMBLe) programme comprised three field experiments. This manuscript presents an overview of the measurements made within the two simultaneous remote experiments conducted in the tropical North Atlantic in May and June 2007. Measurements were made from two mobile and one ground-based platforms. The heavily instrumented cruise D319 on the RRS Discovery from Lisbon, Portugal to São Vicente, Cape Verde and back to Falmouth, UK was used to characterise the spatial distribution of boundary layer components likely to play a role in reactive halogen chemistry. Measurements onboard the ARSF Dornier aircraft were used to allow the observations to be interpreted in the context of their vertical distribution and to confirm the interpretation of atmospheric structure in the vicinity of the Cape Verde islands. Long-term ground-based measurements at the Cape Verde Atmospheric Observatory (CVAO) on São Vicente were supplemented by long-term measurements of reactive halogen species and characterisation of additional trace gas and aerosol species during the intensive experimental period. This paper presents a summary of the measurements made within the RHaMBLe remote experiments and discusses them in their meteorological and chemical context as determined from these three platforms and from additional meteorological analyses. Air always arrived at the CVAO from the North East with a range of air mass origins (European, Atlantic and North American continental). Trace gases were present at stable and fairly low concentrations with the exception of a slight increase in some anthropogenic components in air of North American origin, though NOx mixing ratios during this period remained below 20 pptv (note the non-IUPAC adoption in this manuscript of pptv and ppbv, equivalent to pmol mol−1 and nmol mol−1 to reflect common practice). Consistency with these air mass classifications is observed in the time series of soluble gas and aerosol composition measurements, with additional identification of periods of slightly elevated dust concentrations consistent with the trajectories passing over the African continent. The CVAO is shown to be broadly representative of the wider North Atlantic marine boundary layer; measurements of NO, O3 and black carbon from the ship are consistent with a clean Northern Hemisphere marine background. Aerosol composition measurements do not indicate elevated organic material associated with clean marine air. Closer to the African coast, black carbon and NO levels start to increase, indicating greater anthropogenic influence. Lower ozone in this region is possibly associated with the increased levels of measured halocarbons, associated with the nutrient rich waters of the Mauritanian upwelling. Bromide and chloride deficits in coarse mode aerosol at both the CVAO and on D319 and the continuous abundance of inorganic gaseous halogen species at CVAO indicate significant reactive cycling of halogens. Aircraft measurements of O3 and CO show that surface measurements are representative of the entire boundary layer in the vicinity both in diurnal variability and absolute levels. Above the inversion layer similar diurnal behaviour in O3 and CO is observed at lower mixing ratios in the air that had originated from south of Cape Verde, possibly from within the ITCZ. ECMWF calculations on two days indicate very different boundary layer depths and aircraft flights over the ship replicate this, giving confidence in the calculated boundary layer depth.

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An increasing importance is assigned to the estimation and verification of carbon stocks in forests. Forestry practice has several long-established and reliable methods for the assessment of aboveground biomass; however we still miss accurate predictors of belowground biomass. A major windthrow event exposing the coarse root systems of Norway spruce trees allowed us to assess the effects of contrasting soil stone and water content on belowground allocation. Increasing stone content decreases root/shoot ratio, while soil waterlogging leads to an increase in this ratio. We constructed allometric relationships for belowground biomass prediction and were able to show that only soil waterlogging significantly impacts model parameters. We showed that diameter at breast height is a reliable predictor of belowground biomass and, once site-specific parameters have been developed, it is possible to accurately estimate belowground biomass in Norway spruce.

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Cross-contamination between cell lines is a longstanding and frequent cause of scientific misrepresentation. Estimates from national testing services indicate that up to 36% of cell lines are of a different origin or species to that claimed. To test a standard method of cell line authentication, 253 human cell lines from banks and research institutes worldwide were analyzed by short tandem repeat profiling. The short tandem repeat profile is a simple numerical code that is reproducible between laboratories, is inexpensive, and can provide an international reference standard for every cell line. If DNA profiling of cell lines is accepted and demanded internationally, scientific misrepresentation because of cross-contamination can be largely eliminated.

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Many techniques are currently used for motion estimation. In the block-based approaches the most common procedure applied is the block-matching based on various algorithms. To refine the motion estimates resulting from the full search or any coarse search algorithm, one can find few applications of Kalman filtering, mainly in the intraframe scheme. The Kalman filtering technique applicability for block-based motion estimation is rather limited due to discontinuities in the dynamic behaviour of the motion vectors. Therefore, we propose an application of the concept of the filtering by approximated densities (FAD). The FAD, originally introduced to alleviate limitations due to conventional Kalman modelling, is applied to interframe block-motion estimation. This application uses a simple form of FAD involving statistical characteristics of multi-modal distributions up to second order.