Desempenho operacional e energético, segundo a norma OECD – code 2 de dois tratores agrícolas 4x2 TDA com motores de 132 kw em pista concreto e solo agrícola

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Avaliação do desgalhador florestal de discos em função de diferentes teores de umidade da madeira de eucalipto

Pós-graduação em Ciência Florestal - FCA

Different responses in bulk density and saturated hydraulic conductivity to soil deformation by logging machinery on a Ferralsol under native forest

Ferralsols have high structural stability, although structural degradation has been observed to result from forest to tillage or pasture conversion. An experimental series of forest skidder passes in an east Amazonian natural forest was performed for testing the effects of mechanical stress during selective logging operations on a clay-rich Ferralsol under both dry and wet soil conditions. Distinct ruts formed up to 25 cm depth only under wet conditions. After nine passes the initially very low surface bulk density of between 0.69 and 0.80 g cm(-3) increased to 1.05 g cm(-3) in the wet soil and 0.92 g cm(-3) in the dry soil. Saturated hydraulic conductivities, initially > 250 mm h(-1), declined to a minimum of around 10 mm h(-1) in the wet soil after the first pass, and in the dry soil more gradually after nine passes. The contrasting response of bulk density and saturated hydraulic conductivity is explained by exposure of subsoil material at the base of the ruts where macrostructure rapidly deteriorated under wet conditions. We attribute the resultant moderately high hydraulic conductivities to the formation of stable microaggregates with fine sand to coarse silt textures. We conclude that the topsoil macrostructure of Ferralsols is subject to similar deterioration to that of Luvisols in temperate zones. The stable microstructure prevents marked compaction and decrease in hydraulic conductivity under wetter and more plastic soil conditions. However, typical tropical storms may regularly exceed the infiltration capacity of the deformed soils. In the deeper ruts water may concentrate and cause surface run-off, even in gently sloping areas. To avoid soil erosion, logging operations in sloping areas should therefore be restricted to dry soil conditions when rut formation is minimal.

Expression, Enzymatic Activities and Subcellular Localization of Hepatitis E Virus and Semliki Forest Virus Replicase Proteins

Viruses are submicroscopic, infectious agents that are obligate intracellular parasites. They adopt various types of strategies for their parasitic replication and proliferation in infected cells. The nucleic acid genome of a virus contains information that redirects molecular machinery of the cell to the replication and production of new virions. Viruses that replicate in the cytoplasm and are unable to use the nuclear transcription machinery of the host cell have developed their own transcription and capping systems. This thesis describes replication strategies of two distantly related viruses, hepatitis E virus (HEV) and Semliki Forest virus (SFV), which belong to the alphavirus-like superfamily of positive-strand RNA viruses. We have demonstrated that HEV and SFV share a unique cap formation pathway specific for alphavirus-like superfamily. The capping enzyme first acts as a methyltransferase, catalyzing the transfer of a methyl group from S-adenosylmethionine to GTP to yield m7GTP. It then transfers the methylated guanosine to the end of viral mRNA. Both reactions are virus-specific and differ from those described for the host cell. Therefore, these capping reactions offer attractive targets for the development of antiviral drugs. Additionally, it has been shown that replication of SFV and HEV takes place in association with cellular membranes. The origin of these membranes and the intracellular localization of the components of the replication complex were studied by modern microscopy techniques. It was demonstrated that SFV replicates in cytoplasmic membranes that are derived from endosomes and lysosomes. According to our studies, site for HEV replication seems to be the intermediate compartment which mediates the traffic between endoplasmic reticulum and the Golgi complex. As a result of this work, a unique mechanism of cap formation for hepatitis E virus replicase has been characterized. It represents a novel target for the development of specific inhibitors against viral replication.

Weather variability, tides, and Barmah Forest Virus Disease in the Gladstone region, Australia

In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (β = 0.15, p-value < 0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (β = −1.03, p-value = 0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention.

Particle number and mass emission factors from combustion of wood samples collected from Queensland forest

Knowledge of particle emission characteristics associated with forest fires and in general, biomass burning, is becoming increasingly important due to the impact of these emissions on human health. Of particular importance is developing a better understanding of the size distribution of particles generated from forest combustion under different environmental conditions, as well as provision of emission factors for different particle size ranges. This study was aimed at quantifying particle emission factors from four types of wood found in South East Queensland forests: Spotted Gum (Corymbia citriodora), Red Gum (Eucalypt tereticornis), Blood Gum (Eucalypt intermedia), and Iron bark (Eucalypt decorticans); under controlled laboratory conditions. The experimental set up included a modified commercial stove connected to a dilution system designed for the conditions of the study. Measurements of particle number size distribution and concentration resulting from the burning of woods with a relatively homogenous moisture content (in the range of 15 to 26 %) and for different rates of burning were performed using a TSI Scanning Mobility Particle Sizer (SMPS) in the size range from 10 to 600 nm and a TSI Dust Trak for PM2.5. The results of the study in terms of the relationship between particle number size distribution and different condition of burning for different species show that particle number emission factors and PM2.5 mass emission factors depend on the type of wood and the burning rate; fast burning or slow burning. The average particle number emission factors for fast burning conditions are in the range of 3.3 x 1015 to 5.7 x 1015 particles/kg, and for PM2.5 are in the range of 139 to 217 mg/kg.

At-the-edge-of-the-forest

This exhibition was the outcome of a personal arts-based exploration of the meaning of interiority. Through the process it was found that existentially the architectural wall differentiating inside from outside does not exist but operates as a space of overlap, a groundless ground providing for dwelling in the real existential sense of the word.

Intelligent prognostics of machinery health utilising suspended condition monitoring data

The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

The ideological context of business : capital

This chapter focuses on the major social ruptures and developments that are most significant in the historical emergence and development of Capital and, more precisely, on those ruptures that highlight the most significant ethical issues upon which Capital, as a form of social organisation, is premised. Capital is most often viewed as a system of relationships between “things”, like land, labour, machinery, money, and so on. But this is to obscure the human relationships within which Capital flourishes.