910 resultados para Intermodal Container Terminal, Rail Transportation, Delays, Simulation, Australia


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The widespread and increasing resistance of internal parasites to anthelmintic control is a serious problem for the Australian sheep and wool industry. As part of control programmes, laboratories use the Faecal Egg Count Reduction Test (FECRT) to determine resistance to anthelmintics. It is important to have confidence in the measure of resistance, not only for the producer planning a drenching programme but also for companies investigating the efficacy of their products. The determination of resistance and corresponding confidence limits as given in anthelmintic efficacy guidelines of the Standing Committee on Agriculture (SCA) is based on a number of assumptions. This study evaluated the appropriateness of these assumptions for typical data and compared the effectiveness of the standard FECRT procedure with the effectiveness of alternative procedures. Several sets of historical experimental data from sheep and goats were analysed to determine that a negative binomial distribution was a more appropriate distribution to describe pre-treatment helminth egg counts in faeces than a normal distribution. Simulated egg counts for control animals were generated stochastically from negative binomial distributions and those for treated animals from negative binomial and binomial distributions. Three methods for determining resistance when percent reduction is based on arithmetic means were applied. The first was that advocated in the SCA guidelines, the second similar to the first but basing the variance estimates on negative binomial distributions, and the third using Wadley’s method with the distribution of the response variate assumed negative binomial and a logit link transformation. These were also compared with a fourth method recommended by the International Co-operation on Harmonisation of Technical Requirements for Registration of Veterinary Medicinal Products (VICH) programme, in which percent reduction is based on the geometric means. A wide selection of parameters was investigated and for each set 1000 simulations run. Percent reduction and confidence limits were then calculated for the methods, together with the number of times in each set of 1000 simulations the theoretical percent reduction fell within the estimated confidence limits and the number of times resistance would have been said to occur. These simulations provide the basis for setting conditions under which the methods could be recommended. The authors show that given the distribution of helminth egg counts found in Queensland flocks, the method based on arithmetic not geometric means should be used and suggest that resistance be redefined as occurring when the upper level of percent reduction is less than 95%. At least ten animals per group are required in most circumstances, though even 20 may be insufficient where effectiveness of the product is close to the cut off point for defining resistance.

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By quantifying the effects of climatic variability in the sheep grazing lands of north western and western Queensland, the key biological rates of mortality and reproduction can be predicted for sheep. These rates are essential components of a decision support package which can prove a useful management tool for producers, especially if they can easily obtain the necessary predictors. When the sub-models of the GRAZPLAN ruminant biology process model were re-parameterised from Queensland data along with an empirical equation predicting the probability of ewes mating added, the process model predicted the probability of pregnancy well (86% variation explained). Predicting mortality from GRAZPLAN was less successful but an empirical equation based on relative condition of the animal (a measure based on liveweight), pregnancy status and age explained 78% of the variation in mortalities. A crucial predictor in these models was liveweight which is not often recorded on producer properties. Empirical models based on climatic and pasture conditions estimated from the pasture production model GRASP, predicted marking and mortality rates for Mitchell grass (Astrebla sp.) pastures (81% and 63% of the variation explained). These prediction equations were tested against independent data from producer properties and the model successfully validated for Mitchell grass communities.

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This study investigated the cool roof technology effects on annual energy saving of a large one-storey commercial building in Queensland, Australia. A computer model of the case study was developed using commercial software by using the appropriate geometrical and thermal building specifications. Field study data were used to validate the model. The model was then used to extend the investigation to other cities in various Australian climate zones. The results of this research show that significant energy savings can be obtained using cool roof technology, particularly in warm, sunny climates, and the thesis can contribute to provide a guideline for application of cool roof technology to single-storey commercial building throughout Australia.

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An adaptive conjoint analysis was use to evaluate stakeholders' opinion of welfare indicators for ship-transported sheep and cattle, both onboard and in pre-export depots. In consultations with two nominees of each identified stakeholder group (government officials, animal welfare representatives, animal scientists, stockpersons, producers/pre-export depot operators, exporters/ship owners and veterinarians), 18 potential indicators were identified Three levels were assigned to each using industry statistics and expert opinion, representing those observed on the best and worst 5% of voyages and an intermediate value. A computer-based questionnaire was completed by 135 stakeholders (48% of those invited). All indicators were ranked by respondents in the assigned order, except fodder intake, in which case providing the amount necessary to maintain bodyweight was rated better than over or underfeeding, and time in the pre-export assembly depot, in which case 5 days was rated better than 0 or 10 days. The respective Importance Values (a relative rating given by the respondent) for each indicator were, in order of declining importance: mortality (8.6%), clinical disease incidence (8.2%), respiration rate (6.8%), space allowance (6.2%), ammonia levels (6.1%), weight change (6.0%), wet bulb temperature (6.0%), time in assembly depot (5.4%), percentage of animals in hospital pen (5.4%), fodder intake (5.2%), stress-related metabolites (5.0%), percentage of feeding trough utilised (5.0%), injuries (4.8%), percentage of animals able to access food troughs at any one time (4.8%), percentage of animals lying down (4.7%), cortisol concentration (4.5Y.), noise (3.9y.), and photoperiod (3.4%). The different stakeholder groups were relatively consistent in their ranking of the indicators, with all groups nominating the some top two and at least five of the top seven indicators. Some of the top indicators, in particular mortality, disease incidence and temperature, are already recorded in the Australian industry, but the study identified potential new welfare indicators for exported livestock, such as space allowance and ammonia concentration, which could be used to improve welfare standards if validated by scientific data. The top indicators would also be useful worldwide for countries engaging in long distance sea transport of livestock.

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Quantifying the potential spread and density of an invading organism enables decision-makers to determine the most appropriate response to incursions. We present two linked models that estimate the spread of Solenopsis invicta Buren (red imported fire ant) in Australia based on limited data gathered after its discovery in Brisbane in 2001. A stochastic cellular automaton determines spread within a location (100 km by 100 km) and this is coupled with a model that simulates human-mediated movement of S. invicta to new locations. In the absence of any control measures, the models predict that S. invicta could cover 763 000–4 066 000 km2 by the year 2035 and be found at 200 separate locations around Australia by 2017–2027, depending on the rate of spread. These estimated rates of expansion (assuming no control efforts were in place) are higher than those experienced in the USA in the 1940s during the early invasion phases in that country. Active control efforts and quarantine controls in the USA (including a concerted eradication attempt in the 1960s) may have slowed spread. Further, milder winters, the presence of the polygynous social form, increased trade and human mobility in Australia in 2000s compared with the USA in 1940s could contribute to faster range expansion.

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Ramp metering (RM) is an access control for motorways, in which a traffic signal is placed at on-ramps to regulate the rate of vehicles entering the motorway and thus to preserve the motorway capacity. In general, RM algorithms fall into two categories by their effective scope: local control and coordinated control. Local control algorithm determines the metering rate based on the traffic condition on adjacent motorway mainline and the on-ramp. Conversely, coordinated RM strategies make use of measurements from the entire motorway network to operate individual ramp signals for optimal performance at the network level. This study proposes a multi-hierarchical strategy for on-ramp coordination. The strategy is structured in two layers. At the higher layer, a centralised, predictive controller plans the coordination control within a long update interval based on the location of high-risk breakdown flow. At the lower layer, reactive controllers determine the metering rates of those ramps involved in the ramp coordination with a short update interval. This strategy is modelled and applied to the northbound model of the Pacific Motorway in a micro-simulation platform (AIMSUN). The simulation results show that the proposed strategy effectively delays the onset of congestion and reduces total congestion with better managed on-ramp queues.

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Aim: To develop a surveillance support model that enables prediction of areas susceptible to invasion, comparative analysis of surveillance methods and intensity and assessment of eradication feasibility. To apply the model to identify surveillance protocols for generalized invasion scenarios and for evaluating surveillance and control for a context-specific plant invasion. Location: Australia. Methods: We integrate a spatially explicit simulation model, including plant demography and dispersal vectors, within a Geographical Information System. We use the model to identify effective surveillance protocols using simulations of generalized plant life-forms spreading via different dispersal mechanisms in real landscapes. We then parameterize the surveillance support model for Chilean needle grass [CNG; Nassella neesiana (Trin. & Rupr.) Barkworth], a highly invasive tussock grass, which is an eradication target in south-eastern Queensland, Australia. Results: General surveillance protocols that can guide rapid response surveillance were identified; suitable habitat that is susceptible to invasion through particular dispersal syndromes should be targeted for surveillance using an adaptive seek-and-destroy method. The search radius of the adaptive method should be based on maximum expected dispersal distances. Protocols were used to define a surveillance strategy for CNG, but simulations indicated that despite effective and targeted surveillance, eradication is implausible at current intensities. Main conclusions: Several important surveillance protocols emerged and simulations indicated that effectiveness can be increased if they are followed in rapid response surveillance. If sufficient data are available, the surveillance support model should be parameterized to target areas susceptible to invasion and determine whether surveillance is effective and eradication is feasible. We discovered that for CNG, regardless of a carefully designed surveillance strategy, eradication is implausible at current intensities of surveillance and control and these efforts should be doubled if they are to be successful. This is crucial information in the face of environmentally and economically damaging invasive species and large, expensive and potentially ineffective control programmes.

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Camels (Camelus dromedarius) were introduced into Australia from the 1840s to the early 1900s for transport and hauling cargo in arid regions. Feral populations remained small until the 1930s when many were released after they were superseded for transport by trucks and rail. Although camels have a relatively slow population growth (<10% per annum), the population has not reached carrying capacity and therefore, requires control to reduce the increasing impacts on central Australia. The model developed for the Northern Territory suggested that currently there are insufficient numbers being removed. The model also investigated which control options would have greatest impacts and found harvesting to be most important. The extent to which commercial harvesting can feasibly reduce camel populations requires further analysis. Due to the wide dispersal of camels in Australia, fertility control, even if technically feasible, will not target adults, the most important age class of the population. Habitat preferences were also investigated in the model but more validation is required as the population is still under range expansion. Immediate action is suggested to alleviate future costs as camel populations and their impacts rise.

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Senna obtusifolia (sicklepod) is an invasive weed of northern Australia, where it significantly impacts agricultural productivity and alters natural ecosystem structure and function. Although currently restricted to northern regions, the potential for S. obtusifolia to spread south is not known. Using the eco-climatic model CLIMEX, this study simulated the potential geographic distribution of S. obtusifolia in Australia under two scenarios. Model parameters for both scenarios were derived from the distribution of S. obtusifolia throughout North and Central America. The first scenario used these base model parameters to predict the distribution of S. obtusifolia in Australia, whilst the second model predicted the distribution of a cold susceptible S. obtusifolia ecotype that is reported to occur in the USA. Both models predicted the potential for an extensive S. obtusifolia distribution, with the first model indicating suitable climatic conditions occurring predominantly in coastal regions from the Northern Territory, to far north Queensland and into northern Victoria. The cold susceptible ecotype displayed a comparatively reduced distribution in the southern parts of Australia, where inappropriate temperatures, a lack of thermal accumulation and cold stress restrict the invasion south to the coastal regions of central New South Wales. The extent of the predicted distribution of both ecotypes of S. obtusifolia reinforces the need for strategic management at a national scale.

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Several intelligent transportation systems (ITS) were used with an advanced driving simulator to assess its influence on driving behavior. Three types of ITS interventions were tested: video in vehicle, audio in vehicle, and on-road flashing marker. The results from the driving simulator were inputs for a developed model that used traffic microsimulation (VISSIM 5.4) to assess the safety interventions. Using a driving simulator, 58 participants were required to drive through active and passive crossings with and without an ITS device and in the presence or absence of an approaching train. The effect of changes in driver speed and compliance rate was greater at passive crossings than at active crossings. The slight difference in speed of drivers approaching ITS devices indicated that ITS helped drivers encounter crossings in a safer way. Since the traffic simulation was not able to replicate a dynamic speed change or a probability of stopping that varied depending on ITS safety devices, some modifications were made to the traffic simulation. The results showed that exposure to ITS devices at active crossings did not influence drivers’ behavior significantly according to the traffic performance indicator, such as delay time, number of stops, speed, and stopped delay. However, the results of traffic simulation for passive crossings, where low traffic volumes and low train headway normally occur, showed that ITS devices improved overall traffic performance.

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Wild European rabbits are a serious problem to agriculture in Australia, with an estimated annual cost of A$ 113 million. Biological control agents (myxomatosis and rabbit haemorrhagic disease virus) have caused large and sustained declines in rabbit populations throughout Australia. A simulation model incorporates these diseases as well as warren destruction as methods of controlling rabbit populations in Queensland, north eastern Australia. These diseases reduced populations by 90-99% and the combination of these and warren destruction led to 100% control in simulations at six sites across southern Queensland. Increasing monthly pasture growth by 15% had little effect on simulated populations whereas a 15% decrease reduced populations by 0-50%. An increase in temperature of 2.5 °C would lead to a 15-60% decrease in populations. These effects suggest that climate change will lead to a decrease in the population of rabbits in Queensland and a retraction in the northern limit of their distribution in Australia.

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Because of the variable and changing environment, advisors and farmers are seeking systems that provide risk management support at a number of time scales. The Agricultural Production Systems Research Unit, Toowoomba, Australia has developed a suite of tools to assist advisors and farmers to better manage risk in cropping. These tools range from simple rainfall analysis tools (Rainman, HowWet, HowOften) through crop simulation tools (WhopperCropper and YieldProphet) to the most complex, APSFarm, a whole-farm analysis tool. Most are derivatives of the APSIM crop model. These tools encompass a range of complexity and potential benefit to both the farming community and for government policy. This paper describes, the development and usage of two specific products; WhopperCropper and APSFarm. WhopperCropper facilitates simulation-aided discussion of growers' exposure to risk when comparing alternative crop input options. The user can readily generate 'what-if' scenarios that separate the major influences whilst holding other factors constant. Interactions of the major inputs can also be tested. A manager can examine the effects of input levels (and Southern Oscillation Index phase) to broadly determine input levels that match their attitude to risk. APSFarm has been used to demonstrate that management changes can have different effects in short and long time periods. It can be used to test local advisors and farmers' knowledge and experience of their desired rotation system. This study has shown that crop type has a larger influence than more conservative minimum soil water triggers in the long term. However, in short term dry periods, minimum soil water triggers and maximum area of the various crops can give significant financial gains.

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The nitrogen-driven trade-off between nitrogen utilisation efficiency (yield per unit nitrogen uptake) and water use efficiency (yield per unit evapotranspiration) is widespread and results from well established, multiple effects of nitrogen availability on the water, carbon and nitrogen economy of crops. Here we used a crop model (APSIM) to simulate the yield, evapotranspiration, soil evaporation and nitrogen uptake of wheat, and analysed yield responses to water, nitrogen and climate using a framework analogous to the rate-duration model of determinate growth. The relationship between modelled grain yield (Y) and evapotranspiration (ET) was fitted to a linear-plateau function to derive three parameters: maximum yield (Ymax), the ET break-point when yield reaches its maximum (ET#), and the rate of yield response in the linear phase ([Delta]Y/[Delta]ET). Against this framework, we tested the hypothesis that nitrogen deficit reduces maximum yield by reducing both the rate ([Delta]Y/[Delta]ET) and the range of yield response to evapotranspiration, i.e. ET# - Es, where Es is modelled median soil evaporation. Modelled data reproduced the nitrogen-driven trade-off between nitrogen utilisation efficiency and water use efficiency in a transect from Horsham (36°S) to Emerald (23°S) in eastern Australia. Increasing nitrogen supply from 50 to 250 kg N ha-1 reduced yield per unit nitrogen uptake from 29 to 12 kg grain kg-1 N and increased yield per unit evapotranspiration from 6 to 15 kg grain ha-1 mm-1 at Emerald. The same increment in nitrogen supply reduced yield per unit nitrogen uptake from 30 to 25 kg grain kg-1 N and increased yield per unit evapotranspiration from 6 to 25 kg grain ha-1 mm-1 at Horsham. Maximum yield ranged from 0.9 to 6.4 t ha-1. Consistent with our working hypothesis, reductions in maximum yield with nitrogen deficit were associated with both reduction in the rate of yield response to ET and compression of the range of yield response to ET. Against the notion of managing crops to maximise water use efficiency in low rainfall environments, we emphasise the trade-off between water use efficiency and nitrogen utilisation efficiency, particularly under conditions of high nitrogen-to-grain price ratio. The rate-range framework to characterise the relationship between yield and evapotranspiration is useful to capture this trade-off as the parameters were responsive to both nitrogen supply and climatic factors.

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The closure of abattoirs in Australia dictates that pigs will be transported over greater distances resulting in increased costs and reduced margins for producers. Factors contributing to reduced margins could include increased freight costs, reduced scale weight as a result of reduced killing out percentage and condemnations (due to injuries) plus possible increased deaths in transport. More information is needed in Australia on transport practices and mortalities to address knowledge deficiencies in our understanding of the welfare implications of road transport.

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Parthenium weed (Parthenium hysterophorus L.) is an erect, branched, annual plant of the family Asteraceae. It is native to the tropical Americas, while now widely distributed throughout Africa, Asia, Oceania, and Australasia. Due to its allelopathic and toxic characteristics, parthenium weed has been considered to be a weed of global significance. These effects occur across agriculture (crops and pastures), within natural ecosystems, and has impacts upon health (human and animals). Although integrated weed management (IWM) for parthenium weed has had some success, due to its tolerance and good adaptability to temperature, precipitation, and CO2, this weed has been predicted to become more vigorous under a changing climate resulting in an altered canopy architecture. From the viewpoint of IWM, the altered canopy architecture may be associated with not only improved competitive ability and replacement but also may alter the effectiveness of biocontrol agents and other management strategies. This paper reports on a preliminary study on parthenium weed canopy architecture at three temperature regimes (day/night 22/15 °C, 27/20 °C, and 32/25 °C in thermal time 12/12 hours) and establishes a threedimensional (3D) canopy model using Lindenmayer-systems (L-systems). This experiment was conducted in a series of controlled environment rooms with parthenium weed plants being grown in a heavy clay soil. A sonic digitizer system was used to record the morphology, topology, and geometry of the plants for model construction. The main findings include the determination of the phyllochron which enables the prediction of parthenium weed growth under different temperature regimes and that increased temperature enhances growth and enlarges the plants canopy size and structure. The developed 3D canopy model provides a tool to simulate and predict the weed growth in response to temperature, and can be adjusted for studies of other climatic variables such as precipitation and CO2. Further studies are planned to investigate the effects of other climatic variables, and the predicted changes in the pathogenic biocontrol agent effectiveness.