997 resultados para optimum-path forest (OPF)


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Background: A previous review showed that high stress increases the risk of occupational injury by three- to five-fold. However, most of the prior studies have relied on short follow-ups. In this prospective cohort study we examined the effect of stress on recorded hospitalised injuries in an 8-year follow-up.
Methods: A total of 16,385 employees of a Finnish forest company responded to the questionnaire. Perceived stress was measured with a validated single-item measure, and analysed in relation recorded hospitalised injuries from 1986 to 2008. We used Cox proportional hazard regression models to examine the prospective associations between work stress, injuries and confounding factors.
Results: Highly stressed participants were approximately 40% more likely to be hospitalised due to injury over the follow-up period than participants with low stress. This association remained significant after adjustment for age, gender, marital status, occupational status, educational level, and physical work environment.
Conclusions: High stress is associated with an increased risk of severe injury.

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This study presents the design of a thin electromagnetic absorber which exhibits radar backscatter suppression that is independent of the wave polarisation at large incidence angles. The structure consists of a metal backed printed frequency selective surface (FSS), with resistors placed across narrow gaps inserted in the middle of each of the four sides of the conductor loops. The geometry of the periodic array and the value of the vertical and horizontal resistor pairs are carefully chosen to present a real impedance of 377 Ω at the centre operating frequency for both TE and TM polarised waves. Angular sensitivity and reflectivity bandwidth have been investigated for FSS absorber designs with thicknesses of 1, 2 and 3 mm. Each of the three structures was optimised to work at a centre frequency of 10 GHz and an incident angle of 45°. The design methodology is verified by measuring the radar backscatter suppression from a 3 mm (l / 10) thick screen in the frequency range 8–12 GHz. The absorber construction was simplified by filling the four metal gaps in each unit cell with shielding paint, and selecting the ink thickness to give the two required surface resistance values.

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The emerging tephrostratigraphy of NW Europe spanning the last termination (ca. 15–9 ka) provides the potential for synchronizing marine, ice-core and terrestrial records, but is currently compromised by stratigraphic complications, geochemical ambiguity and imprecise age estimates for some layers. Here we present new tephrostratigraphic, radiocarbon and chironomid-based
palaeotemperature data from Abernethy Forest, Scotland, that refine the ages and stratigraphic positions of the Borrobol and Penifiler tephras. The Borrobol Tephra (14.14–13.95 cal ka BP) was deposited in a relatively warm period equated with Greenland Interstadial sub-stage GI-1e. The younger Penifiler Tephra (14.09–13.65 cal ka BP) is closely associated with a cold oscillation equated with GI-
1d. We also present evidence for a previously undescribed tephra layer that has a major-element chemical signature identical to the Vedde Ash. It is associated with the warming trend at the end of the Younger Dryas, and dates between 11.79 and 11.20 cal ka BP.

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Compacted clay fills are generally placed at the optimum value of water content and, immediately after placement, they are unsaturated. Wetting might subsequently occur due, for example, to rainfall infiltration, which can cause volumetric deformation of the fill (either swell or collapse) with associated loss of shear strength and structural integrity. If swelling takes place under partially restrained deformation, due for example to the presence of a buried rigid structure or a retaining wall, additional stresses will develop in the soil and these can be detrimental to the stability of walling elements and other building assets. Factors such as dry density, overburden pressure, compaction water content and type of clay are known to influence the development of stresses. This paper investigates these factors by means of an advanced stress path testing programme performed on four different clays with different mineralogy, index properties and geological histories. Specimens of kaolin clay, London Clay, Belfast Clay and Ampthill Clay were prepared at different initial states and subjected to ‘controlled’ wetting, whereby the suction was reduced gradually to zero under laterally restrainedconditions (i.e. K0 conditions). The results showed that the magnitude of the increase in horizontal stresses (and therefore the increase of K0) is influenced by the overburden pressure, compaction water content, dry density at the time of compaction and mineralogy.

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The reaction mechanism of CO and Fe2O3 in a chemical-looping combustion (CLC) was studied based on density functional theory (DFT) at B3LYP level in this paper. The structures of all reactants, intermediate, transition structures and products of this reaction had been optimized and characterized. The reaction path was validated by means of the intrinsic reaction coordinate (IRC) approach. The result showed that the reaction was divided into two steps, the adsorbed CO molecule on Fe 2O3 surface formed a medium state with one broken Fe-O bond in step1, and in step2, O atom broken here oxidized a subsequent CO molecule in the fuel reactor. Thus, Fe2O3 molecule transport O from air to oxide CO continually in the CLC process. The activation energy and rate coefficients of the two steps were also obtained.

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Artificial neural network (ANN) methods are used to predict forest characteristics. The data source is the Southeast Alaska (SEAK) Grid Inventory, a ground survey compiled by the USDA Forest Service at several thousand sites. The main objective of this article is to predict characteristics at unsurveyed locations between grid sites. A secondary objective is to evaluate the relative performance of different ANNs. Data from the grid sites are used to train six ANNs: multilayer perceptron, fuzzy ARTMAP, probabilistic, generalized regression, radial basis function, and learning vector quantization. A classification and regression tree method is used for comparison. Topographic variables are used to construct models: latitude and longitude coordinates, elevation, slope, and aspect. The models classify three forest characteristics: crown closure, species land cover, and tree size/structure. Models are constructed using n-fold cross-validation. Predictive accuracy is calculated using a method that accounts for the influence of misclassification as well as measuring correct classifications. The probabilistic and generalized regression networks are found to be the most accurate. The predictions of the ANN models are compared with a classification of the Tongass national forest in southeast Alaska based on the interpretation of satellite imagery and are found to be of similar accuracy.