60 resultados para Two-level scheduling and optimization
Resumo:
Sainfoin (Onobrychis viciifolia) is a condensed tannin (CT)-containing legume and has anthelmintic potential against gastrointestinal nematodes of ruminants. This study investigated in vitro effects of acetone/water extracts and derived CT fractions from different types of sainfoin (i.e. accessions) against larvae of Cooperia oncophora and Ostertagia ostertagi by applying the larval feeding inhibition assay (LFIA). Seven sainfoin accessions were extracted and tested with L1 larvae at 10 and 40 μg extract/ml. In addition, CT in extracts from 4 accessions were fractionated according to polymer size and tested by LFIA at two concentrations (2 and 10 μg CT fraction/ml). All sainfoin extracts caused significant inhibition of L1-feeding of both C. oncophora and O. ostertagi with varying intensity compared to the control (phosphate buffered saline). For both nematode species the in vitro effect was positively correlated with CT content in the extracts, but not with any of the structural CT parameters. In contrast, the 16 CT fractions revealed significant correlations between in vitro effect and CT content, polymer size (mean degree of polymerisation, mDP) and monomeric composition (prodelphinidin percentage, % PD). These differences between crude extracts and purified fractions may stem from the fact that extracts contain complex CT mixtures, which may mask and thus suppress CT structural effects. This study provides the first indication that, apart from CT and % PD content, polymer size also contributes to anthelmintic activity of CTs. The results, therefore, suggest that the inter-accession variability in CT content and composition needs to be taken into account in future plant breeding programmes which seek to enhance the anthelmintic properties of sainfoin
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Hourly data (1994–2009) of surface ozone concentrations at eight monitoring sites have been investigated to assess target level and long–term objective exceedances and their trends. The European Union (EU) ozone target value for human health (60 ppb–maximum daily 8–hour running mean) has been exceeded for a number of years for almost all sites but never exceeded the set limit of 25 exceedances in one year. Second highest annual hourly and 4th highest annual 8–hourly mean ozone concentrations have shown a statistically significant negative trend for in–land sites of Cork–Glashaboy, Monaghan and Lough Navar and no significant trend for the Mace Head site. Peak afternoon ozone concentrations averaged over a three year period from 2007 to 2009 have been found to be lower than corresponding values over a three–year period from 1996 to 1998 for two sites: Cork–Glashaboy and Lough Navar sites. The EU long–term objective value of AOT40 (Accumulated Ozone Exposure over a threshold of 40 ppb) for protection of vegetation (3 ppm–hour, calculated from May to July) has been exceeded, on an individual year basis, for two sites: Mace Head and Valentia. The critical level for the protection of forest (10 ppm–hour from April to September) has not been exceeded for any site except at Valentia in the year 2003. AOT40–Vegetation shows a significant negative trend for a 3–year running average at Cork–Glashaboy (–0.13±0.02 ppm–hour per year), at Lough Navar (–0.05±0.02 ppm–hour per year) and at Monaghan (–0.03±0.03 ppm–hour per year–not statistically significant) sites. No statistically significant trend was observed for the coastal site of Mace head. Overall, with the exception of the Mace Head and Monaghan sites, ozone measurement records at Irish sites show a downward negative trend in peak values that affect human health and vegetation.
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Interactions between different convection modes can be investigated using an energy–cycle description under a framework of mass–flux parameterization. The present paper systematically investigates this system by taking a limit of two modes: shallow and deep convection. Shallow convection destabilizes itself as well as the other convective modes by moistening and cooling the environment, whereas deep convection stabilizes itself as well as the other modes by drying and warming the environment. As a result, shallow convection leads to a runaway growth process in its stand–alone mode, whereas deep convection simply damps out. Interaction between these two convective modes becomes a rich problem, even when it is limited to the case with no large–scale forcing, because of these opposing tendencies. Only if the two modes are coupled at a proper level can a self–sustaining system arise, exhibiting a periodic cycle. The present study establishes the conditions for self–sustaining periodic solutions. It carefully documents the behaviour of the two mode system in order to facilitate the interpretation of global model behaviours when this energy–cycle is implemented as a closure into a convection parameterization in future.
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We have incorporated a semi-mechanistic isoprene emission module into the JULES land-surface scheme, as a first step towards a modelling tool that can be applied for studies of vegetation – atmospheric chemistry interactions, including chemistry-climate feedbacks. Here, we evaluate the coupled model against local above-canopy isoprene emission flux measurements from six flux tower sites as well as satellite-derived estimates of isoprene emission over tropical South America and east and south Asia. The model simulates diurnal variability well: correlation coefficients are significant (at the 95 % level) for all flux tower sites. The model reproduces day-to-day variability with significant correlations (at the 95 % confidence level) at four of the six flux tower sites. At the UMBS site, a complete set of seasonal observations is available for two years (2000 and 2002). The model reproduces the seasonal pattern of emission during 2002, but does less well in the year 2000. The model overestimates observed emissions at all sites, which is partially because it does not include isoprene loss through the canopy. Comparison with the satellite-derived isoprene-emission estimates suggests that the model simulates the main spatial patterns, seasonal and inter-annual variability over tropical regions. The model yields a global annual isoprene emission of 535 ± 9 TgC yr−1 during the 1990s, 78 % of which from forested areas.
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A novel two-stage construction algorithm for linear-in-the-parameters classifier is proposed, aiming at noisy two-class classification problems. The purpose of the first stage is to produce a prefiltered signal that is used as the desired output for the second stage to construct a sparse linear-in-the-parameters classifier. For the first stage learning of generating the prefiltered signal, a two-level algorithm is introduced to maximise the model's generalisation capability, in which an elastic net model identification algorithm using singular value decomposition is employed at the lower level while the two regularisation parameters are selected by maximising the Bayesian evidence using a particle swarm optimization algorithm. Analysis is provided to demonstrate how “Occam's razor” is embodied in this approach. The second stage of sparse classifier construction is based on an orthogonal forward regression with the D-optimality algorithm. Extensive experimental results demonstrate that the proposed approach is effective and yields competitive results for noisy data sets.
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This paper explores the mapping of the environmental assessment process onto design and construction processes. A comparative case study method is used to identify and account for variations in the ‘fit’ between these two processes. The analysis compares eight BREEAM projects (although relevant to LEED, GreenStar, etc.) and distinguishes project-level characteristics and dynamics. Drawing on insights from literature on sustainable construction and assessment methods, an analytic framework is developed to examine the effect of clusters of project and assessment level elements on different types of fit (tight, punctual and bolt-on). Key elements distinguishing between types include: prior working experience with project team members, individual commitment to sustainable construction, experience with sustainable construction, project continuity, project-level ownership of the assessment process, and the nature and continuity of assessor involvement. Professionals with ‘sustainable’ experience used BREEAM judiciously to support their designs (along with other frameworks), but less committed professionals tended to treat it purely as an assessment method. More attention needs to be paid to individual levels of engagement with, and understanding of, sustainability in general (rather than knowledge of technical solutions to individual credits), to ownership of the assessment process and to the potential effect of discontinuities at the project level on sustainable design.
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This letter has tested the canopy height profile (CHP) methodology as a way of effective leaf area index (LAIe) and vertical vegetation profile retrieval at a single-tree level. Waveform and discrete airborne LiDAR data from six swaths, as well as from the combined data of six swaths, were used to extract the LAIe of a single live Callitris glaucophylla tree. LAIe was extracted from raw waveform as an intermediate step in the CHP methodology, with two different vegetation-ground reflectance ratios. Discrete point LAIe estimates were derived from the gap probability using the following: 1) single ground returns and 2) all ground returns. LiDAR LAIe retrievals were subsequently compared to hemispherical photography estimates, yielding mean values within ±7% of the latter, depending on the method used. The CHP of a single dead Callitris glaucophylla tree, representing the distribution of vegetation material, was verified with a field profile manually reconstructed from convergent photographs taken with a fixed-focal-length camera. A binwise comparison of the two profiles showed very high correlation between the data reaching R2 of 0.86 for the CHP from combined swaths. Using a study-area-adjusted reflectance ratio improved the correlation between the profiles, but only marginally in comparison to using an arbitrary ratio of 0.5 for the laser wavelength of 1550 nm.
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In Britain, managed grass lawns provide the most traditional and widespread of garden and landscape practices in use today. Grass lawns are coming under increasing challenge as they tend to support a low level of biodiversity and can require substantial additional inputs to maintain. Here we apply a novel approach to the traditional monocultural lawnscape by replacing grasses entirely with clonal perennial forbs. We monitored changes in plant coverage and species composition over a two year period and here we report the results of a study comparing plant origin native, non-native and mixed) and mowing regime. This allows us to assess the viability of this construct as an alternative to traditional grass lawns. Grass-free lawns provided a similar level of plant cover to grass lawns. Both the mowing regime and the combination of species used affected this outcome, with native plant species seen to have the highest survival rates, and mowing at 4cm to produce the greatest amount of ground coverage and plant species diversity within grass-free lawns. Grass-free lawns required over 50% less mowing than a traditionally managed grass lawn. Observations suggest that plant forms that exhibited: a) a relatively fast growth rate, b) a relatively large individual leaf area, and c) an average leaf height substantially above the cut to be applied, were unsuitable for use in grass-free lawns. With an equivalent level of ground coverage to grass lawns, increased plant diversity and a reduced need for mowing, the grass-free lawn can be seen as a species diverse, lower input and potentially highly ornamental alternative to the traditional lawn format.
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Purpose – Characteristics of leaders whose behaviour is visceral include taking action based on instinct rather than intellect and exhibiting coarse, base and often negative emotions. Despite the challenge of precisely defining the nature of visceral behaviour, the purpose of this paper is to provide insight into this less attractive side of boardroom life. Design/methodology/approach – Following a literature review of the research into the negative behaviour leaders exhibit, the paper highlights four forms of visceral behaviour based on focused and intimate qualitative case studies involving the experiences of those on the receiving end of that behaviour within a boardroom context. Findings – Based on interviews with an international sample of five chief executive officers (CEOs), plus three subordinates with substantial profit and loss responsibility, the study reveals a distinctly human experience from which no one is exempt. The idiosyncratic nature of the visceral behaviour experienced resulted in each study participant's unique experience. The authors conclude that leaders need to adopt specific measures in order to control and reduce the darker human tendencies. Research limitations/implications – The experiences of study participants are presented in four case studies, providing insight into their experiences whilst also protecting their identity. The study participants were drawn from a sample of companies operating globally within a single sector of the manufacturing industry. The concepts the authors present require validating in other organisations with different demographic profiles. Originality/value – The paper presents a model based on two dimensions – choice and level of mastery – that provides the reader with insight into the forms of visceral behaviour to which leaders succumb. Insight enables us to offer managers strategic suggestions to guard against visceral behaviour and assist them in mitigating its worst aspects, in both those with whom they work and themselves.
Resumo:
Predictions of twenty-first century sea level change show strong regional variation. Regional sea level change observed by satellite altimetry since 1993 is also not spatially homogenous. By comparison with historical and pre-industrial control simulations using the atmosphere–ocean general circulation models (AOGCMs) of the CMIP5 project, we conclude that the observed pattern is generally dominated by unforced (internal generated) variability, although some regions, especially in the Southern Ocean, may already show an externally forced response. Simulated unforced variability cannot explain the observed trends in the tropical Pacific, but we suggest that this is due to inadequate simulation of variability by CMIP5 AOGCMs, rather than evidence of anthropogenic change. We apply the method of pattern scaling to projections of sea level change and show that it gives accurate estimates of future local sea level change in response to anthropogenic forcing as simulated by the AOGCMs under RCP scenarios, implying that the pattern will remain stable in future decades. We note, however, that use of a single integration to evaluate the performance of the pattern-scaling method tends to exaggerate its accuracy. We find that ocean volume mean temperature is generally a better predictor than global mean surface temperature of the magnitude of sea level change, and that the pattern is very similar under the different RCPs for a given model. We determine that the forced signal will be detectable above the noise of unforced internal variability within the next decade globally and may already be detectable in the tropical Atlantic.
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This study investigated the effects of increased genetic diversity in winter wheat (Triticum aestivum L.), either from hybridization across genotypes or from physical mixing of lines, on grain yield, grain quality, and yield stability in different cropping environments. Sets of pure lines (no diversity), chosen for high yielding ability or high quality, were compared with line mixtures (intermediate level of diversity), and lines crossed with each other in composite cross populations (CCPn, high diversity). Additional populations containing male sterility genes (CCPms) to increase outcrossing rates were also tested. Grain yield, grain protein content, and protein yield were measured at four sites (two organically-managed and two conventionally-managed) over three years, using seed harvested locally in each preceding year. CCPn and mixtures out-yielded the mean of the parents by 2.4% and 3.6%, respectively. These yield differences were consistent across genetic backgrounds but partly inconsistent across cropping environments and years. Yield stability measured by environmental variance was higher in CCPn and CCPms than the mean of the parents. An index of yield reliability tended to be higher in CCPn, CCPms and mixtures than the mean of the parents. Lin and Binns’ superiority values of yield and protein yield were consistently and significantly lower (i.e. better) in the CCPs than in the mean of the parents, but not different between CCPs and mixtures. However, CCPs showed greater early ground cover and plant height than mixtures. When compared with the (locally non-predictable) best-yielding pure line, CCPs and mixtures exhibited lower mean yield and somewhat lower yield reliability but comparable superiority values. Thus, establishing CCPs from smaller sets of high-performing parent lines might optimize their yielding ability. On the whole, the results demonstrate that using increased within-crop genetic diversity can produce wheat crops with improved yield stability and good yield reliability across variable and unpredictable cropping environments.
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The advance of the onset of the Indian monsoon is here explained in terms of a balance between the low-level monsoon flow and an over-running intrusion of mid-tropospheric dry air. The monsoon advances, over a period of about 6 weeks, from the south of the country to the northwest. Given that the low-level monsoon winds are westerly or southwesterly, and the midlevel winds northwesterly, the monsoon onset propagates upwind relative to midlevel flow, and perpendicular to the low-level flow, and is not directly caused by moisture flux toward the northwest. Lacking a conceptual model for the advance means that it has been hard to understand and correct known biases in weather and climate prediction models. The mid-level northwesterlies form a wedge of dry air that is deep in the far northwest of India and over-runs the monsoon flow. The dry layer is moistened from below by shallow cumulus and congestus clouds, so that the profile becomes much closer to moist adiabatic, and the dry layer is much shallower in the vertical, toward the southeast of India. The profiles associated with this dry air show how the most favourable environment for deep convection occurs in the south, and onset occurs here first. As the onset advances across India, the advection of moisture from the Arabian Sea becomes stronger, and the mid-level dry air is increasingly moistened from below. This increased moistening makes the wedge of dry air shallower throughout its horizontal extent, and forces the northern limit of moist convection to move toward the northwest. Wetting of the land surface by rainfall will further reinforce the north-westward progression, by sustaining the supply of boundary layer moisture and shallow cumulus. The local advance of the monsoon onset is coincident with weakening of the mid-level northwesterlies, and therefore weakened mid-level dry advection.
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This paper presents the two datasets (ARENA and P5) and the challenge that form a part of the PETS 2015 workshop. The datasets consist of scenarios recorded by us- ing multiple visual and thermal sensors. The scenarios in ARENA dataset involve different staged activities around a parked vehicle in a parking lot in UK and those in P5 dataset involve different staged activities around the perimeter of a nuclear power plant in Sweden. The scenarios of each dataset are grouped into ‘Normal’, ‘Warning’ and ‘Alarm’ categories. The Challenge specifically includes tasks that account for different steps in a video understanding system: Low-Level Video Analysis (object detection and tracking), Mid-Level Video Analysis (‘atomic’ event detection) and High-Level Video Analysis (‘complex’ event detection). The evaluation methodology used for the Challenge includes well-established measures.
Resumo:
The variation of wind-optimal transatlantic flight routes and their turbulence potential is investigated to understand how upper-level winds and large-scale flow patterns can affect the efficiency and safety of long-haul flights. In this study, the wind-optimal routes (WORs) that minimize the total flight time by considering wind variations are modeled for flights between John F. Kennedy International Airport (JFK) in New York, New York, and Heathrow Airport (LHR) in London, United Kingdom, during two distinct winter periods of abnormally high and low phases of North Atlantic Oscillation (NAO) teleconnection patterns. Eastbound WORs approximate the JFK–LHR great circle (GC) route following northerly shifted jets in the +NAO period. Those WORs deviate southward following southerly shifted jets during the −NAO period, because eastbound WORs fly closely to the prevailing westerly jets to maximize tailwinds. Westbound WORs, however, spread meridionally to avoid the jets near the GC in the +NAO period to minimize headwinds. In the −NAO period, westbound WORs are north of the GC because of the southerly shifted jets. Consequently, eastbound WORs are faster but have higher probabilities of encountering clear-air turbulence than westbound ones, because eastbound WORs are close to the jet streams, especially near the cyclonic shear side of the jets in the northern (southern) part of the GC in the +NAO (−NAO) period. This study suggests how predicted teleconnection weather patterns can be used for long-haul strategic flight planning, ultimately contributing to minimizing aviation’s impact on the environment
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A dynamical wind-wave climate simulation covering the North Atlantic Ocean and spanning the whole 21st century under the A1B scenario has been compared with a set of statistical projections using atmospheric variables or large scale climate indices as predictors. As a first step, the performance of all statistical models has been evaluated for the present-day climate; namely they have been compared with a dynamical wind-wave hindcast in terms of winter Significant Wave Height (SWH) trends and variance as well as with altimetry data. For the projections, it has been found that statistical models that use wind speed as independent variable predictor are able to capture a larger fraction of the winter SWH inter-annual variability (68% on average) and of the long term changes projected by the dynamical simulation. Conversely, regression models using climate indices, sea level pressure and/or pressure gradient as predictors, account for a smaller SWH variance (from 2.8% to 33%) and do not reproduce the dynamically projected long term trends over the North Atlantic. Investigating the wind-sea and swell components separately, we have found that the combination of two regression models, one for wind-sea waves and another one for the swell component, can improve significantly the wave field projections obtained from single regression models over the North Atlantic.