Diversity of zooplankton assemblages at Station L4, Western English Channel, measured using next generation DNA sequencing

Background: Zooplankton play an important role in our oceans, in biogeochemical cycling and providing a food source for commercially important fish larvae. However, difficulties in correctly identifying zooplankton hinder our understanding of their roles in marine ecosystem functioning, and can prevent detection of long term changes in their community structure. The advent of massively parallel Next Generation Sequencing technology allows DNA sequence data to be recovered directly from whole community samples. Here we assess the ability of such sequencing to quantify the richness and diversity of a mixed zooplankton assemblage from a productive monitoring site in the Western English Channel. Methodology/Principle Findings: Plankton WP2 replicate net hauls (200 µm) were taken at the Western Channel Observatory long-term monitoring station L4 in September 2010 and January 2011. These samples were analysed by microscopy and metagenetic analysis of the 18S nuclear small subunit ribosomal RNA gene using the 454 pyrosequencing platform. Following quality control a total of 419,042 sequences were obtained for all samples. The sequences clustered in to 205 operational taxonomic units using a 97% similarity cut-off. Allocation of taxonomy by comparison with the National Centre for Biotechnology Information database identified 138 OTUs to species level, 11 to genus level and 1 to order, <2.5% of sequences were classified as unknowns. By comparison a skilled microscopic analyst was able to routinely enumerate only 75 taxonomic groups. Conclusions: The percentage of OTUs assigned to major eukaryotic taxonomic groups broadly aligns between the metagenetic and morphological analysis and are dominated by Copepoda. However, the metagenetics reveals a previously hidden taxonomic richness, especially for Copepoda and meroplankton such as Bivalvia, Gastropoda and Polychaeta. It also reveals rare species and parasites. We conclude that Next Generation Sequencing of 18S amplicons is a powerful tool for estimating diversity and species richness of zooplankton communities.

Table 1 Microorganisms, identified with DOGE analysis. 16S rDNA sequences, obtained from sequencing of DOGE bands, were assigned to the corresponding microorganisms

Microorganisms play an important role in the transformation of material within the earth's crust. The storage of CO2 could affect the composition of inorganic and organic components in the reservoir, consequently influencing microbial activities. To study the microbial induced processes together with geochemical, petrophysical and mineralogical changes, occurring during CO2 storage, long-term laboratory experiments under simulated reservoir P-T conditions were carried out. Clean inner core sections, obtained from the reservoir region at the CO2 storage site in Ketzin (Germany) from a depth of about 650 m, were incubated in high pressure vessels together with sterile synthetic formation brine under in situ P-T conditions of 5.5 MPa and 40°C. A 16S rDNA based fingerprinting method was used to identify the dominant species in DNA extracts of pristine sandstone samples. Members of the alpha- and beta-subdivisions of Proteobacteria and the Actinobacteria were identified. So far sequences belonging to facultative anaerobic, chemoheterotrophic bacteria (Burkholderia fungorum, Agrobacterium tumefaciens) gaining their energy from the oxidation of organic molecules and a genus also capable of chemolithoautotrophic growth (Hydrogenophaga) was identified. During CO2 incubation minor changes in the microbial community composition were observed. The majority of microbes were able to adapt to the changed conditions. During CO2 exposure increased concentrations of Ca**2+, K**+, Mg**2+ and SO4**2- were observed. Partially, concentration rises are (i) due to equilibration between rock pore water and synthetic brine, and (ii) between rock and brine, and are thus independent on CO2 exposure. However, observed concentrations of Ca**2+, K**+, Mg**2+ are even higher than in the original reservoir fluid and therefore indicate mineral dissolution due to CO2 exposure.

Molecular fingerprinting and amplicon sequencing of the bacterial biofilm on settlement tiles deployed along natural pH gradients in Papua New Guinea

Bacterial biofilms provide cues for the settlement of marine invertebrates such as coral larvae, and are therefore important for the resilience and recovery of coral reefs. This study aimed to better understand how ocean acidification may affect the community composition and diversity of bacterial biofilms on surfaces under naturally reduced pH conditions. Settlement tiles were deployed at coral reefs in Papua New Guinea along pH gradients created by two CO2 seeps, and upper and lower tiles surfaces were sampled 5 and 13 months after deployment. Automated Ribosomal Intergenic Spacer Analysis were used to characterize more than 200 separate bacterial communities, complemented by amplicon sequencing of the bacterial 16S rRNA gene of 16 samples. The bacterial biofilm consisted predominantly of Alpha-, Gamma- and Deltaproteobacteria, as well as Cyanobacteria, Flavobacteriia and Cytophaga, whereas putative settlement-inducing taxa only accounted for a small fraction of the community. Bacterial biofilm composition was heterogeneous with approximately 25% shared operational taxonomic units between samples. Among the observed environmental parameters, pH only had a weak effect on community composition (R² ~ 1%) and did not affect community richness and evenness. In contrast, there were strong differences between upper and lower surfaces (contrasting in light exposure and grazing intensity). There also appeared to be a strong interaction between bacterial biofilm composition and the macroscopic components of the tile community. Our results suggest that on mature settlement surfaces in situ, pH does not have a strong impact on the composition of bacterial biofilms. Other abiotic and biotic factors such as light exposure and interactions with other organisms may be more important in shaping bacterial biofilms than changes in seawater pH.

A Visual AGV-Urban Car using Fuzzy Control

The goal of the work described in this paper is to develop a visual line guided system for being used on-board an Autonomous Guided Vehicle (AGV) commercial car, controlling the steering and using just the visual information of a line painted below the car. In order to implement the control of the vehicle, a Fuzzy Logic controller has been implemented, that has to be robust against curvature changes and velocity changes. The only input information for the controller is the visual distance from the image center captured by a camera pointing downwards to the guiding line on the road, at a commercial frequency of 30Hz. The good performance of the controller has successfully been demonstrated in a real environment at urban velocities. The presented results demonstrate the capability of the Fuzzy controller to follow a circuit in urban environments without previous information about the path or any other information from additional sensors

Influence of driving style on fuel consumption and Emissions in diesel-powered passenger car

This paper presents the main results of a study on the influence of driving style on fuel consumption and pollutant emissions of diesel passenger car in urban traffic. Driving styles (eco, normal or aggressive) patterns were based on the “eco-driving” criteria. The methodology is based on on-board emission measurements in real urban traffic in the city of Madrid. Five diesel passenger cars, have been tested. Through a statistical analysis, a Dynamic Performance Index was defined for diesel passenger cars. Likewise, the CO, NOX and HC emissions were compared for each driving style for the tested vehicles. Eco-driving reduces by 14% fuel consumption and CO2 emissions, but aggressive driving increase consumption by 40%. Aggressive driving increases NOX emission by more than 40%. CO and HC, show different trends, but being increased in eco-driving style.

Proposal of a dynamic performance index to analyze driving pattern effect on car emissions

The contributions of driver behaviour as well as surrounding infrastructure are decisive on pollutant emissions from vehicles in real traffic situations. This article deals with the preliminary study of the interaction between the dynamic variables recorded in a vehicle (driving pattern) and pollutant emissions produced over a given urban route. It has been established a “dynamic performance index”-DPI, which is calculated from some driving pattern parameters, which in turn depends on traffic congestion level and route characteristics, in order to determine whether the driving has been aggressive, normal or calm. Two passenger cars instrumented with a portable activity measurement system -to record dynamic variables- and on-board emission measurement equipment have been used. This study has shown that smooth driving patterns can reduce up to 80% NOX emissions and up to 20% of fuel in the same route

Intensive use of aluminium in car body construction

The developments in materials over the last decade have been considerable within the automotive industry, being one of the leaders in innovative product applications. Sustainable product development of an automotive structure requires a balanced approach towards technological, economical and ecological aspects. The introduction of new materials and processes is dependent on satisfying different factors. Competitive and legislative pressures, creating the need for change, affect these factors considerably. The process, direction and speed of change are often reactive. Current paper shows the application of aluminium alloys, for the use in the bottom structure of a car to face the problem for the weight of the entire bottom structure under static load conditions, including stiffness, strength and buckling constraints. In addition to minimized mass and materials' price, the assessment of an environmental impact of materials-candidates during the entire life cycle of the structure is considered.

Car Carrier 5.800 TPM

Tipo de Buque: Car Carrier. Capacidad de carga: carga 1: 3000 coches sin trailers. Carga 2: Carga combinada para 1500 ml de trailers y coches en el resto de las cubiertas del buque no ocupadas por los trailers. Peso muerto 5800 TPM. Capacidad de conductores: 100 personas en camarotes dobles. Sociedad de clasificación: Det Norske Veritas. Reglamentos: Solas, Marpol, Convenio de líneas de carga. Velocidad: 19 nudos al 85% MCR en pruebas. Autonomía: 4500 millas al 80% MCR y 15% al margen de mar. Tripulación 25 personas.

A simulation method to estimate closing forces in car-sealing rubber elements

The door-closing process can reinforce the impression of a solid, rock-proof, car body or of a rather cheap, flimsy vehicle. As there are no real prototypes during rubber profile bidding-out stages, engineers need to carry out non-linear numerical simulations that involve complex phenomena as well as static and dynamic loads for several profile candidates. This paper presents a structured virtual design tool based on FEM, including constitutive laws and incompressibility constraints allowing to predict more realistically the final closing forces and even to estimate sealing overpressure as an additional guarantee of noise insulation. Comparisons with results of physical tests are performed.

Floating car data augmentation based on infrastructure sensors and neural networks

The development of new-generation intelligent vehicle technologies will lead to a better level of road safety and CO2 emission reductions. However, the weak point of all these systems is their need for comprehensive and reliable data. For traffic data acquisition, two sources are currently available: 1) infrastructure sensors and 2) floating vehicles. The former consists of a set of fixed point detectors installed in the roads, and the latter consists of the use of mobile probe vehicles as mobile sensors. However, both systems still have some deficiencies. The infrastructure sensors retrieve information fromstatic points of the road, which are spaced, in some cases, kilometers apart. This means that the picture of the actual traffic situation is not a real one. This deficiency is corrected by floating cars, which retrieve dynamic information on the traffic situation. Unfortunately, the number of floating data vehicles currently available is too small and insufficient to give a complete picture of the road traffic. In this paper, we present a floating car data (FCD) augmentation system that combines information fromfloating data vehicles and infrastructure sensors, and that, by using neural networks, is capable of incrementing the amount of FCD with virtual information. This system has been implemented and tested on actual roads, and the results show little difference between the data supplied by the floating vehicles and the virtual vehicles.