Evaluation of terrain collision risks for flight style autonomous underwater vehicles

Photographic surveys of the seafloor with flight style autonomous underwater vehicles are a very effective tool for discovery and exploration. Due to the high terrain collision risk for the survey vehicle, they are employed with caution. The extent of this risk remains unquantified. For mission planning, researchers and vehicle operators have to rely on their experience. This paper introduces measures for vehicle risk and success and analyses how previously mapped terrains and artificially generated terrain maps can be used to categorize terrains. The developed measures are applied to a simulation of the Autosub6000 flight style AUV terrain following system. Based on quantitative parameters, changes to the obstacle avoidance system and survey mission plans can be better informed

Control of an AUV from thruster actuated hover to control surface actuated flight

An autonomous underwater vehicle (AUV) capable of both low speed hovering and high speed flight-style operation is introduced. To have this capability the AUV is over-actuated with a rear propeller, four control surfaces and four through-body tunnel thrusters. In this work the actuators are modelled and the non-linearities and uncertainties are identified and discussed with specific regard to operation at different speeds. A thruster-actuated depth control algorithm and a flight-style control-surface actuated depth controller are presented. These controllers are then coupled using model reference feedback to enable transition between the two controllers to enable vehicle stability throughout the speed range. Results from 3 degrees-of-freedom simulations of the AUV using the new controller are presented, showing that the controller works well to smoothly transition between controllers. The performance of the depth controller appears asymmetric with better performance whilst diving than ascendin

Complex Risks from Old Urban Waste Landfills: Sustainability Perspective from Iasi, Romania

Landfills continue to represent the most frequent managerial practice for municipal solid wastes and an increasing and complex problem globally. In certain countries, a transition to an open society and free market is superimposed on the transition to sustainability, resulting in even higher complexity of management. This paper proposes an approach for problem-structuring of landfills in complex transitions: sustainability or unsustainability of a management approach is determined by a set of sustainability filters that are defined by sets of indicators and prioritized according the systemic concept of sustainability, which says that economy is embedded in society, which is embedded in nature. The writers exercise this approach with an old landfill in Iasi, Romania, and conclude for unsustainability, because the ecological sustainability filter is not successfully passed. Social and economic sustainability filters are also discussed in relation with the ecological sustainability indicators. The described approach allows a coherent, transdisciplinary synthesis of knowledge scattered across various disciplines, a pervasive problem in landfill management. The case study helps distinguish between generally true and context-dependent aspects.Peer reviewe

The impact of European legislative and technology measures to reduce air pollutants on air quality, human health and climate

European air quality legislation has reduced emissions of air pollutants across Europe since the 1970s, affecting air quality, human health and regional climate. We used a coupled composition-climate model to simulate the impacts of European air quality legislation and technology measures implemented between 1970 and 2010. We contrast simulations using two emission scenarios; one with actual emissions in 2010 and the other with emissions that would have occurred in 2010 in the absence of technological improvements and end-of-pipe treatment measures in the energy, industrial and road transport sectors. European emissions of sulphur dioxide, black carbon (BC) and organic carbon in 2010 are 53%, 59% and 32% lower respectively compared to emissions that would have occurred in 2010 in the absence of legislative and technology measures. These emission reductions decreased simulated European annual mean concentrations of fine particulate matter(PM2.5) by 35%, sulphate by 44%, BC by 56% and particulate organic matter by 23%. The reduction in PM2.5 concentrations is calculated to have prevented 80 000 (37 000–116 000, at 95% confidence intervals) premature deaths annually across the European Union, resulting in a perceived financial benefit to society of US$232 billion annually (1.4% of 2010 EU GDP). The reduction in aerosol concentrations due to legislative and technology measures caused a positive change in the aerosol radiative effect at the top of atmosphere, reduced atmospheric absorption and also increased the amount of solar radiation incident at the surface over Europe. We used an energy budget approximation to estimate that these changes in the radiative balance have increased European annual mean surface temperatures and precipitation by 0.45 ± 0.11 °C and by 13 ± 0.8 mm yr−1 respectively. Our results show that the implementation of European legislation and technological improvements to reduce the emission of air pollutants has improved air quality and human health over Europe, as well as having an unintended impact on the regional radiative balance and climate

High-confidence glycosome proteome for procyclic form <em>Trypanosoma brucei</em> by epitope-tag organelle enrichment and SILAC proteomics

The glycosome of the pathogenic African trypanosome Trypanosoma brucei is a specialized peroxisome that contains most of the enzymes of glycolysis and several other metabolic and catabolic pathways. The contents and transporters of this membrane-bounded organelle are of considerable interest as potential drug targets. Here we use epitope tagging, magnetic bead enrichment, and SILAC quantitative proteomics to determine a high-confidence glycosome proteome for the procyclic life cycle stage of the parasite using isotope ratios to discriminate glycosomal from mitochondrial and other contaminating proteins. The data confirm the presence of several previously demonstrated and suggested pathways in the organelle and identify previously unanticipated activities, such as protein phosphatases. The implications of the findings are discussed

The disruption of GDP-fucose de novo biosynthesis suggests the presence of a novel fucose-containing glycoconjugate in <i>Plasmodium</i> asexual blood stages

Glycosylation is an important posttranslational protein modification in all eukaryotes. Besides glycosylphosphatidylinositol (GPI) anchors and N-glycosylation, O-fucosylation has been recently reported in key sporozoite proteins of the malaria parasite. Previous analyses showed the presence of GDP-fucose (GDP-Fuc), the precursor for all fucosylation reactions, in the blood stages of Plasmodium falciparum. The GDP-Fuc de novo pathway, which requires the action of GDP-mannose 4,6-dehydratase (GMD) and GDP-L-fucose synthase (FS), is conserved in the parasite genome, but the importance of fucose metabolism for the parasite is unknown. To functionally characterize the pathway we generated a PfGMD mutant and analyzed its phenotype. Although the labelling by the fucose-binding Ulex europaeus agglutinin I (UEA-I) was completely abrogated, GDP-Fuc was still detected in the mutant. This unexpected result suggests the presence of an alternative mechanism for maintaining GDP-Fuc in the parasite. Furthermore, PfGMD null mutant exhibited normal growth and invasion rates, revealing that the GDP-Fuc de novo metabolic pathway is not essential for the development in culture of the malaria parasite during the asexual blood stages. Nonetheless, the function of this metabolic route and the GDP-Fuc pool that is generated during this stage may be important for gametocytogenesis and sporogonic development in the mosquito

The impact of self-monitoring in chronic illness on healthcare utilisation: a systematic review of reviews

Background: Self-management interventions have been found to reduce healthcare utilisation in people with long-term conditions, but further work is needed to identify which components of these interventions are most effective. Self-monitoring is one such component and is associated with significant clinical benefits. The aim of this systematic review of reviews is to assess the impact of self-monitoring interventions on healthcare utilisation across a range of chronic illnesses. Methods: An overview of published systematic reviews and meta-analyses. Multiple databases were searched (MEDLINE, CINAHL, PsycINFO, EMBASE, AMED, EBM and HMIC) along with the reference lists of included reviews. A narrative synthesis was performed, accompanied by calculation of the Corrected Cover Area to understand the impact of overlapping primary research papers. Results: A total of 17 systematic reviews and meta-analyses across three chronic conditions, heart failure, hypertension and chronic obstructive pulmonary disease, were included. Self-monitoring was associated with significant reductions in hospitalisation and re-admissions to hospital. Conclusions: Self-monitoring has the potential to reduce the pressure placed on secondary care services, but this may lead to increase in services elsewhere in the system. Further work is needed to determine how these findings affect healthcare costs

Ship speed prediction based on machine learning for efficient shipping operation

Optimizing ship operational performance has generated considerable research interest recently to reduce fuel consumption and its associated cost and emissions. One of the key factors to optimize ship design and operation is an accurate prediction of ship speed due to its significant influence on the ship operational efficiency. Traditional methods of ship speed estimation include theoretical calculations, numerical modeling, simulation, or experimental work which can be expensive, time-consuming, have limitations and uncertainties, or it cannot be applied to ships under different operational conditions. Therefore, in this study, a data-driven machine learning approach is investigated for ship speed prediction through regression utilizing a high-quality publicly-accessible ship operational dataset of the ‘M/S Smyril’ ferry. Employed regression algorithms include linear regression, regression trees with different sizes, regression trees ensembles, Gaussian process regression, and support vector machines using different covariance functions implemented in MATLAB and compared in terms of speed prediction accuracy. A comprehensive data preprocessing pipeline of operational features selection, extraction, engineering and scaling is also proposed. Moreover, cross validation, sensitivity analyses, correlation analyses, and numerical simulations are performed. It has been demonstrated that the proposed approach can provide accurate prediction of ship speed under real operational conditions and help in optimizing ship operational parameters

Development of a multi-scheme energy management strategy for a hybrid fuel cell driven passenger ship

Hybrid fuel cell propulsion systems for marine applications are attracting widespread interest due to the need to reduce ship emissions. In order to increase the potential of these systems, the design of an efficient energy management strategy (EMS) is essential to distribute the required power properly between different components of the hybrid system. For a hybrid fuel cell/battery passenger ship, a multi-scheme energy managements strategy is proposed. This strategy is developed using four schemes which are: state-based EMS, equivalent fuel consumption minimization strategy (ECMS), charge-depleting charge-sustaining (CDCS) EMS, the classical proportional-integral (PI) controller based EMS, in addition to a code that chooses the suitable scheme according to the simulation inputs. The main objective of the proposed multi-scheme EMS is to minimize the total consumed energy of the hybrid system in order to increase the energy efficiency of the ship. The world's first fuel cell passenger ship FCS Alsterwasser is considered and its hybrid propulsion system is modelled in MATLAB/Simulink environment. The performance of the developed multi-scheme EMS is compared to the four studied strategies in terms of total consumed energy, hydrogen consumption, total cost and the stresses seen by the hybrid fuel cell/battery system components considering a daily ship operation of 8 h. Results indicate that a maximum energy and hydrogen consumption savings of 8% and 16.7% respectively can be achieved using the proposed multi-scheme strategy