A seakeeping analysis method for an air-lifted vessel

A seakeeping analysis in the frequency domain is presented to predict the motion response of an airlifted vessel (ALV) in waves. The ALV is supported by pressurised air in two separate cushion chambers; the pressure variation in the cushions has a significant effect on the motions of the vessel. The adiabatic gas law is used to couple cushion pressure and the free-surface elevation of water inside the chamber. Attention is focused on the waves generated by the pressure, and a method is presented to compute the corresponding free-surface elevation. New numerical schemes are proposed for calculating the threedimensional free-surface elevation for the four wave numbers. Numerical results of the free-surface elevation, escape area, escape volume and motion responses of the ALV are provided. & 2008 Elsevier Ltd. All rights reserved

Some implications of sampling choices on comparisons between satellite and model aerosol optical depth fields

The comparison of satellite and model aerosol optical depth (AOD) fields provides useful information on the strengths and weaknesses of both. However, the sampling of satellite and models is very different and some subjective decisions about data selection and aggregation must be made in order to perform such comparisons. This work examines some implications of these decisions, using GlobAerosol AOD retrievals at 550 nm from Advanced Along-Track Scanning Radiometer (AATSR) measurements, and aerosol fields from the GEOS-Chem chemistry transport model. It is recommended to sample the model only where the satellite flies over on a particular day; neglecting this can cause regional differences in model AOD of up to 0.1 on monthly and annual timescales. The comparison is observed to depend strongly upon thresholds for sparsity of satellite retrievals in the model grid cells. Requiring at least 25% coverage of the model grid cell by satellite data decreases the observed difference between the two by approximately half over land. The impact over ocean is smaller. In both model and satellite datasets, there is an anticorrelation between the proportion <i>p</i> of a model grid cell covered by satellite retrievals and the AOD. This is attributed to small <i>p</i> typically occuring due to high cloud cover and lower AODs being found in large clear-sky regions. Daily median AATSR AODs were found to be closer to GEOS-Chem AODs than daily means (with the root mean squared difference being approximately 0.05 smaller). This is due to the decreased sensitivity of medians to outliers such as cloud-contaminated retrievals, or aerosol point sources not included in the model

MCMC simulation for modelling airline passenger choice behaviour

As passengers we would prefer to pay the cheapest fare available for our airline ticket. On the other hand airline companies wish to increase their revenue from its flown tickets. During the booking process of an airline flight, some passengers may arrive early to book their seats, others may decide to book just few days before departure or even on the day of departure. Airlines realise that they have to offer a variety of fares in order to differentiate between different types of passengers. Allocating seats to different fare classes for different types of passengers in such a way that would maximise the airline’s revenue requires yield/revenue management systems. There are two main steps in any revenue management system: Forecasting and Optimisation. Accurate prediction of passenger future demand for different fare classes improves the seat allocation recommendations resulting from the optimisation step. The work in this thesis concentrates on studying and analysing the behaviour of different passenger types towards different fare classes. We first formulate a Monte Carlo simulation model for the booking process. The model generates sample booking data for a flight on different fare classes by different types of passengers defined by the characteristics which affect their behaviour. Passenger behaviour is modelled using a customer utility function and a multinomial logit (logistic) model of demand. This sample booking data is then used in a Markov Chain Monte Carlo model in order to estimate the passenger choice parameters used in generating the booking data. These estimated parameters could be used then to classify any new booking data. The MCMC model uses the Metropolis Algorithm for its estimation process. We also examine briefly the computational feasibility of our approach using parallel processing

Metabolic Alkalosis

Metabolic alkalosis is a disorder where the primary defect, an increase in plasma bicarbonate concentration, leads to an increase in systemic pH. Here we review the causes of metabolic alkalosis with an emphasis on the inherited causes, namely Gitelman syndrome and Bartter syndrome and syndromes which mimic them. We detail the importance of understanding the kidney pathophysiology and molecular genetics in order to distinguish these syndromes from acquired causes. In particular we discuss the tubular transport of salt in the thick ascending limb of the loop of Henle, the distal convoluted tubule and the collecting duct. The effects of salt wasting, namely an increase in the renin-angiotensin-aldosterone axis are discussed in order to explain the biochemical phenotypes and targeted treatment approaches to these conditions

2015 Forest Resources Assessment shows positive global trends but forest loss and degradation persist in poor tropical countries

The Global Forest Resources Assessment 2015 shows that deforestation has slowed and afforestation has increased globally during 1990–2015. Planted forests have increasingly provided goods and services hitherto derived from natural forests, and mosaic forests in agricultural landscapes are increasing. Forest gain is occurring at higher latitudes and in richer countries whilst forest loss continues in poor countries in the tropics. Some middle income tropical countries are now also transitioning to forest gain. These transition countries are characterised by reforms to forest management and improvements in agricultural practices but also by significant expansions of planted forest, which account for ∼25–100% of gains. Forest-area estimates of the FRA align with satellite-derived estimates, with deviations of ⩽±7% globally and ⩽±17% for the tropics. Mosaics comprised of trees outside forests, remnant forest patches, and young regenerating forests constitute a modest proportion of the tropical forest estate and are seemingly well inventoried by the FRA. Extensive areas of forest experienced partial canopy cover reduction since 2000, particularly in the tropics where their area is ∼6.5 times that deforested since 1990. The likelihood of the eventual loss of these forests and a decline in their capacity to provide goods and services is a matter of concern. Demand for industrial wood and fuelwood increased 35% in the tropics since 1990, principally in poorer countries, and growth in demand will accelerate into the future, particularly in the Asia-Pacific region. Notwithstanding significant increases in forests within protected areas since 1990 to 517 Mha (16.3%) globally and 379 Mha (26.6%) in the tropics, increasing demands for ecological services, forest products, and climate change mitigation is likely to be met from an expanding area of planted forests more than from the declining area of natural forests, particularly in Africa. The global rate of planted-forest expansion since 1990 is close to a target rate of 2.4% per annum necessary to replace wood supplied from natural forests in the medium term, though the expansion rate has declined to 1.5% since 2005. Multiple-use forests permitting both production and conservation account for 26% of the global forest area and 17% of the tropical forest area, and have increased by 81.8 Mha or 8.5% globally since 1990, with most gains in the tropics. Sustainable forest management in low-income and tropical countries remains modest, with only 37% low-income country forests covered by forest inventories. International support has proven effective at increasing this coverage since 2010

Cystinuria: A Review of Inheritance Patterns, Diagnosis, Medical Treatment and Prevention of Stones

Cystinuria is a rare inherited renal stone disease. Mutations in two genes SLC3A1 and SLC7A9 underlie this condition, encoding proteins that facilitate dibasic amino acid exchange which are expressed in the gut and the proximal tubule of the kidney. Genetic studies now allow precise genotyping of patients who may have both autosomal dominant and autosomal recessive patterns of disease. The disorder is characterised by the urinary loss of cystine, lysine, ornithine, and arginine, and the insolubility of cystine gives rise to crystalluria and cysteine-containing renal stones. Although an inherited condition, it may present at any age. Clinical management combines lifestyle advice and preventative medical therapy. However, many patients require surgical interventions to remove problematic stones from the urinary tract. Preventative therapies include increased fluid intake, alkalinization of the urine, and the use of cystine-binding drugs, including penicillamine and tiopronin, which form soluble heterodimers with cystine

The brow-antlered deer in Burma—its distribution and status

Two of the three subspecies of brow-antlered deer are endangered and only the Burmese subspecies is still relatively abundant. Even so, it is a species of major concern in Burma. The authors describe the results of their surveys to determine the deer's status, the main threats to its survival and what needs to be done to conserve i

Modelling of chemical shrinkage evolution with curing degree of a filled epoxy adhesive

An epoxy adhesive system, commonly used in wind turbine blade manufacturing, is experimentally investigated with respect to its chemical shrinkage behavior to show the shrinkage evolution within rotor blade production related process conditions. Therefore, a new test configuration is set up to record the resulting chemical shrinkage of the adhesive at cross-linking temperatures ranging from 20 C to 90 C. The respective conversion evolution is simulated under several temperature conditions through a curing kinetics model. This is generated with state of the art formulations, implementing test results from a differential scanning calorimeter (DSC). Moreover, the transformation of the curing degree to the corresponding glass transition temperature (Tg ) is performed through an experimentally based Di-Benedetto curve-fitting. By the combination of curing kinetics and chemical shrinkage test data, a model for the temperature and conversion dependant chemical shrinkage evolution during cure is developed. This is applied to a realistic curing cycle for adhesive materials in rotor blade production