156 resultados para handling


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Most airports internationally have implemented customer satisfaction programs into their operations to increase non-aeronautical revenues. In the US, taxicabs are an essential airport transport mode given the limited public transport options available. Effective airport taxicab planning can increase airport customer satisfaction levels, as well as facilitate handling increased airport passenger volumes. However, little is known on how US airports have adapted their governance practices from a traditional hierarchical to a network approach in their efforts to undertake airport taxicab planning initiatives since the deregulation of the transportation industry. Data acquired from 51 US hub airports is used to examine their existing taxicab planning practices. The findings offer how US airports can modify governance processes in their airport taxicab planning processes to better support increases in the customer satisfaction levels of airport taxicab patrons.

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Fundamental understanding on microscopic physical changes of plant materials is vital to optimize product quality and processing techniques, particularly in food engineering. Although grid-based numerical modelling can assist in this regard, it becomes quite challenging to overcome the inherited complexities of these biological materials especially when such materials undergo critical processing conditions such as drying, where the cellular structure undergoes extreme deformations. In this context, a meshfree particle based model was developed which is fundamentally capable of handling extreme deformations of plant tissues during drying. The model is built by coupling a particle based meshfree technique: Smoothed Particle Hydrodynamics (SPH) and a Discrete Element Method (DEM). Plant cells were initiated as hexagons and aggregated to form a tissue which also accounts for the characteristics of the middle lamella. In each cell, SPH was used to model cell protoplasm and DEM was used to model the cell wall. Drying was incorporated by varying the moisture content, the turgor pressure, and cell wall contraction effects. Compared to the state of the art grid-based microscale plant tissue drying models, the proposed model can be used to simulate tissues under excessive moisture content reductions incorporating cell wall wrinkling. Also, compared to the state of the art SPH-DEM tissue models, the proposed model better replicates real tissues and the cell-cell interactions used ensure efficient computations. Model predictions showed good agreement both qualitatively and quantitatively with experimental findings on dried plant tissues. The proposed modelling approach is fundamentally flexible to study different cellular structures for their microscale morphological changes at dehydration.

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Thraustochytrids have become of considerable industrial and scientific interest in the past decade due to their health benefits. They have been proven to be the principle source in marine and estuarine fish diets with high percentage of long chain (LC) or polyunsaturated fatty acids (PUFA). Therefore, the oil extracted from fish for human document.forms[0].elements[13].select();consumption is rich in PUFA with high omega-3 fatty acid content. Docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) of all of the omega-3 fatty acids, are considered beneficial essential oils for humans with a wide range of health benefits. These include brain and neural development in infants, general wellbeing of adults and drug delivery through precursor molecules. They have become one of the most extensively studied organisms for industrial oil preparations as PUFA extraction from fish becomes less profitable. Many forms of these Thraustochytrid oils are being trialled for human consumption all over the world. In Australia, there has been little research performed on these organisms in the past ten years. A few Australian studies have been conducted in the form of comparative studies related to PUFA production within the related genera, but not focussed on their identification or cellular and genomic characterisation. Therefore, the main aim of this study was to investigate the morphological and genetic characteristics of Australian Thraustochytrids in order to aid in their identification and characterisation, as well as to better understand the effect of environmental conditions in the regulation of PUFA production. It was also noted that there was a knowledge gap in the preservation and total genomic DNA extraction of these organisms for the purposes of scientific research. The cryopreservation of these organisms for studies around the world follows existing generic methods. However, it is well understood that many of these generic methods attract not only high costs for chemicals, but also uses considerable storage space and other resources, all of which can be improved with new or modified approaches. In this context, a simple and inexpensive bead preservation method is described, without compromising the storage shelf life. We also describe, for the first time, the effects of culture age on the successful cryopreservation of Thraustochytrids. It was evident in the literature that DNA and RNA extractions for molecular and genetic studies of Thraustochytrids follow the classical phenol-chloroform extraction methods. It was also observed that modern protocols failed to avoid the use of phenol-chloroform rather than improving preparation and cell disruption. In order to provide a high quantity and quality DNA extraction, a modified protocol has been introduced that employs the use of modern commercial extraction kits and standard laboratory equipment. Thraustochytrids have been shown to be highly conserved in their 18S rDNA gene sequences, which is used as the current standard for identification. It was demonstrated that the 18S rDNA gene sequence limits the recognition of closely related genera or within the genera from each member. Therefore, it was proposed that another profile, such as a randomly amplified polymorphic DNA (RAPD) based profiling system, be tested for use in the characterisation of Thraustochytrids. The RAPD profiles were shown to provide a unique DNA fingerprint for each isolate and small variations in their genome were able to be detected. This method involved the use of a minimum number of standard arbitrary primers and with an increase in the number of different primers used, a very high discrimination between organisms could be achieved. However, the method was not suitable for taxonomic purposes because the results did not correlate with other taxonomic features such as morphology. Another knowledge gap was found with respect to Australian Thraustochytrid growth characteristics, in that these had not been recorded and published. In order to rectify this, a record of colony and microscopic features of 12 selected isolates was performed. The results of preliminary studies indicated that further microbiological and biochemical studies are needed for full characterisation of these organisms. This information is of great importance to bio-prospecting of new Thraustochytrids from Australian ecosystems and would allow for their accurate identification, and so permit the prediction of their PUFA capability by comparison with related genera/species. It was well recognized that environmental stress plays a role in the PUFA production and is mainly due to the reactive oxygen species as abiotic stress (Chiou et al., 2001; Okuyama et al., 2008; Shabala et al., 2009; Shabala et al., 2001). In this aspect, this study makes the first attempt towards better understanding of this phenomenon by way of the use of real-time PCR for the detection of environmental effects on the regulation of PUFA production. Three main environmental conditions including temperature, pH and oxygen availability were monitored as stress inducers. In summary, this study provides novel approaches for the preservation and handling of Thraustochytrids, their molecular biological features, taxonomy, characterisation and responses to environmental factors with respect to their oil production enzymes. The information produced from this study will prove to be vital for both industrial and scientific investigations in the future.

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A cohort of 59 persons with industrial handling of low levels of acrylonitrile is being studied as part of a medical surveillance programme. Previously, an extended haemoglobin adduct monitoring (N-(cyanoethyl)valine and N-(hydroxyethyl)-valine) was performed regarding the glutathione transferases hGSTM1 and hGSTT1 polymorphisms but no influence of hGSTM1 or hGSTT1 polymorphisms on specific adduct levels was found. A compilation of case reports of human accidental poisonings had pointed to significant individual differences in human acrylonitrile metabolism and toxicity. Therefore, a re-evaluation of the industrial cohort included known polymorphisms of the glutathione transferases hGSTM3 and hGSTP1 as well as of the cytochrome P450 CYP2E1. A detailed statistical analysis revealed that exposed carriers of the allelic variants of hGSTP1, hGSTP1*B/hGSTP1*C, characterized by a single nucleotide polymorphism at nucleotide 313 which results in a change from Ile to Val at codon 104, had higher levels of the acrylonitrile-specific haemoglobin adduct N-(cyanoethyl)valine compared to the carriers of the codon 113 alleles hGSTP1*A and hGSTP1*D. The single nucleotide polymorphism at codon 113 of hGSTP1 (hGSTP1*A/hGSTP1*B versus hGSTP1*C/hGSTP1*D) did not show an effect, and also no influence was seen on specific haemoglobin adduct levels of the polymorphisms of hGSTM3 or CYP2E1. The data, therefore, point to a possible influence of a human enzyme polymorphism of the GSTP1 gene at codon 104 on the detoxication of acrylonitrile which calls for experimental toxicological investigation. The study also confirmed the impact of GSTT1 polymorphism on background N-(hydroxyethyl)-valine adduct levels in haemoglobin which are caused by endogenous ethylene oxide.

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Fifty-nine persons with industrial handling of low levels of acrylonitrile (AN) were studied. As part of a medical surveillance programme an extended haemoglobin adduct monitoring [N-(cyanoethyl)valine, CEV; N- (methyl)valine, MV; N-(hydroxyethyl)valine, HEV] was performed. Moreover, the genetic states of the polymorphic glutathione transferases GSTM1 and GSTT1 were assayed by polymerase chain reaction (PCR). Repetitive analyses of CEV and MV in subsequent years resulted in comparable values (means, 59.8 and 70.3 μg CEV/1 blood; 6.7 and 6.7 μg MV/1 blood). Hence, the industrial AN exposures were well below current official standards. Monitoring the haemoglobin adduct CEV appears as a suitable means of biomonitoring and medical surveillance under such exposure conditions. There was also no apparent correlation between the CEV and HEV or CEV and MV adduct levels. The MV and HEV values observed represented background levels, which apparently are not related to any occupational chemical exposure. There was no consistent effect of the genetic GSTM1 or GSTT1 state on CEV adduct levels induced by acrylonitrile exposure. Therefore, neither GSTM1 nor GSTT1 appears as a major AN metabolizing isoenzyme in humans. The low and physiological background levels of MV were also not influenced by the genetic GSTM1 state, but the MV adduct levels tended to be higher in GSTT1- individuals compared to GSTT1 + persons. With respect to the background levels of HEV adducts observed, there was no major influence of the GSTM1 state, but GST- individuals displayed adduct levels that were about 1/3 higher than those of GSTT1+ individuals. The coincidence with known differences in rates of background sister chromatid exchange between GSTT1- and GSTT1 + persons suggests that the lower ethylene oxide (EO) detoxification rate in GSTT1- persons, indicated by elevated blood protein hydroxyethyl adduct levels, leads to an increased genotoxic effect of the physiological EO background.

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Case reports of human accidental poisonings point to significant individual differences in human acrylonitrile metabolism and toxicity. A cohort of 59 persons with industrial handling of low levels of acrylonitrile has repetitively been studied from 1994 through 1999 as part of a medical surveillance programme. The analyses included adduct determinations of N-terminal N-(cyanoethyl)valine in haemoglobin and genotypings of the following cytochrome P-450 2E1 (CYP2E1) polymorphisms: G-1259C and C-1019T (two subjects heterozygous), A-316G (three subjects heterozygous), T-297A (15 subjects heterozygous), G-35T (eight subjects heterozygous), G4804A (two subjects heterozygous), T7668A (six subjects heterozygous). N-(Cyanoethyl)valine adduct levels were, if any, only slightly influenced by smoking and mainly determined by the external acrylonitrile exposures. The individual means and medians of N-(cyanoethyl)valine levels over the entire observation period were compared with the CYP2E1 variants (Wilcoxon rank sum test). No influences of the investigated CYP2E1 polymorphisms on the N-(cyanoethyl)valine levels appeared at the 5% level. However, there was a trend, at a level of P≃0.1, pointing to higher acrylonitrile-specific adduct levels in persons with the A-316G mutation. Higher adduct levels would be compatible with a slower CYP2E1-mediated metabolism of acrylonitrile and with lower extents of toxification to cyanide.

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Analytically or computationally intractable likelihood functions can arise in complex statistical inferential problems making them inaccessible to standard Bayesian inferential methods. Approximate Bayesian computation (ABC) methods address such inferential problems by replacing direct likelihood evaluations with repeated sampling from the model. ABC methods have been predominantly applied to parameter estimation problems and less to model choice problems due to the added difficulty of handling multiple model spaces. The ABC algorithm proposed here addresses model choice problems by extending Fearnhead and Prangle (2012, Journal of the Royal Statistical Society, Series B 74, 1–28) where the posterior mean of the model parameters estimated through regression formed the summary statistics used in the discrepancy measure. An additional stepwise multinomial logistic regression is performed on the model indicator variable in the regression step and the estimated model probabilities are incorporated into the set of summary statistics for model choice purposes. A reversible jump Markov chain Monte Carlo step is also included in the algorithm to increase model diversity for thorough exploration of the model space. This algorithm was applied to a validating example to demonstrate the robustness of the algorithm across a wide range of true model probabilities. Its subsequent use in three pathogen transmission examples of varying complexity illustrates the utility of the algorithm in inferring preference of particular transmission models for the pathogens.

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In this paper, a method of thrust allocation based on a linearly constrained quadratic cost function capable of handling rotating azimuths is presented. The problem formulation accounts for magnitude and rate constraints on both thruster forces and azimuth angles. The advantage of this formulation is that the solution can be found with a finite number of iterations for each time step. Experiments with a model ship are used to validate the thrust allocation system.

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Rapid development of plug-in hybrid electric vehicles (PHEVs) brings new challenges and opportunities to the power industry. A large number of idle PHEVs can potentially be employed to form a distributed energy storage system for supporting renewable generation. To reduce the negative effects of unsteady renewable generation outputs, a stochastic optimization-based dispatch model capable of handling uncertain outputs of PHEVs and renewable generation is formulated in this paper. The mathematical expectations, second-order original moments, and variances of wind and photovoltaic (PV) generation outputs are derived analytically. Incorporated all the derived uncertainties, a novel generation shifting objective is proposed. The cross-entropy (CE) method is employed to solve this optimal dispatch model. Multiple patterns of renewable generation depending on seasons and renewable market shares are investigated. The feasibility and efficiency of the developed optimal dispatch model, as well as the CE method, are demonstrated with a 33-node distribution system.

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The Sydney rock oyster (Saccostrea glomerata) (SRO) is an oyster species that only occurs in estuaries along Australia's east coast. The SRO industry evolved from commercial gathering of oyster in the 1790s to a high production volume aquaculture industry in the 1970s. However, since the late 1970s the SRO industry has experienced a significant and continuous decline in production quantities and the industry's future commercial viably appears to be uncertain. The aim of this study was to review the history and the status of the SRO industry and to discuss the potential future prospects of this industry. This study summarised findings of the existing literature about the industry and defined development stages of the industry. Particular focus was put on the more recent development within the industry (1980s-present) which has not been covered adequately in the existing literature. The finding from this study revealed that major issues of the industry are linked to the management of prevailing diseases, the handling of water quality impairments from increasing coastal development, increasing competition from Australia's Pacific oyster (Crassostrea gigas) industry and the current socio-economic profile of the industry. The study also found that policy makers are currently confronted by the dilemma of saving a "dying art". Findings from this industry review may be vital for current and future fisheries managers and stakeholders as a basis for reviewing industry management and development strategies. This review may also be of interest for other aquaculture industries and fisheries who are dealing with similar challenges as the SRO industry.

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This thesis develops an operational decision support tool for container terminal managements. The tool generates efficient schedules for shore cranes handling containers carried by mega container vessels.

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Hot metal carriers (HMCs) are large forklift-type vehicles used to move molten metal in aluminum smelters. This paper reports on field experiments that demonstrate that HMCs can operate autonomously and in particular can use vision as a primary sensor to locate the load of aluminum. We present our complete system but focus on the vision system elements and also detail experiments demonstrating reliable operation of the materials handling task. Two key experiments are described, lasting 2 and 5 h, in which the HMC traveled 15 km in total and handled the load 80 times.

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This paper reports work on the automation of a hot metal carrier, which is a 20 tonne forklift-type vehicle used to move molten metal in aluminium smelters. To achieve efficient vehicle operation, issues of autonomous navigation and materials handling must be addressed. We present our complete system and experiments demonstrating reliable operation. One of the most significant experiments was five-hours of continuous operation where the vehicle travelled over 8 km and conducted 60 load handling operations. Finally, an experiment where the vehicle and autonomous operation were supervised from the other side of the world via a satellite phone network are described.

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Stochastic modelling is critical in GNSS data processing. Currently, GNSS data processing commonly relies on the empirical stochastic model which may not reflect the actual data quality or noise characteristics. This paper examines the real-time GNSS observation noise estimation methods enabling to determine the observation variance from single receiver data stream. The methods involve three steps: forming linear combination, handling the ionosphere and ambiguity bias and variance estimation. Two distinguished ways are applied to overcome the ionosphere and ambiguity biases, known as the time differenced method and polynomial prediction method respectively. The real time variance estimation methods are compared with the zero-baseline and short-baseline methods. The proposed method only requires single receiver observation, thus applicable to both differenced and un-differenced data processing modes. However, the methods may be subject to the normal ionosphere conditions and low autocorrelation GNSS receivers. Experimental results also indicate the proposed method can result on more realistic parameter precision.

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Background Climate change may affect mortality associated with air pollutants, especially for fine particulate matter (PM2.5) and ozone (O3). Projection studies of such kind involve complicated modelling approaches with uncertainties. Objectives We conducted a systematic review of researches and methods for projecting future PM2.5-/O3-related mortality to identify the uncertainties and optimal approaches for handling uncertainty. Methods A literature search was conducted in October 2013, using the electronic databases: PubMed, Scopus, ScienceDirect, ProQuest, and Web of Science. The search was limited to peer-reviewed journal articles published in English from January 1980 to September 2013. Discussion Fifteen studies fulfilled the inclusion criteria. Most studies reported that an increase of climate change-induced PM2.5 and O3 may result in an increase in mortality. However, little research has been conducted in developing countries with high emissions and dense populations. Additionally, health effects induced by PM2.5 may dominate compared to those caused by O3, but projection studies of PM2.5-related mortality are fewer than those of O3-related mortality. There is a considerable variation in approaches of scenario-based projection researches, which makes it difficult to compare results. Multiple scenarios, models and downscaling methods have been used to reduce uncertainties. However, few studies have discussed what the main source of uncertainties is and which uncertainty could be most effectively reduced. Conclusions Projecting air pollution-related mortality requires a systematic consideration of assumptions and uncertainties, which will significantly aid policymakers in efforts to manage potential impacts of PM2.5 and O3 on mortality in the context of climate change.