Proglacial river dataset from the Akuliarusiarsuup Kuua River northern tributary, Southwest Greenland, 2008 - 2013, version 2.0

The dataset contains measurements of river stage and discharge for one sites along the Akuliarusiarsuup Kuua River's northern tributary, with 30 minute temporal resolution between June 2008 and August 2013 This river is a tributary to the Watson River discharging into Kangerlussuaq Fjord by the town of Kangerlussuaq, Southwest Greenland. Additional data of water temperature, air pressure are also provided. Compared to version 1.0 of the dataset, this dataset used a total of 36 in situ discharge observations collected between 2008 and 2012 to construct the rating curve. Furthermore, data of Station AK-004-001 between 2010-09-06T11:30 to 2010-09-07T13:30 have been removed from version 2.0 because these values were likely caused by backflow when a jokulhlaup from a large glacier dammed lake caused increased water levels in the downstreams lake. Thus, data measured at AK-004-001 between 2010-09-06T11:30 to 2010-09-07T13:30 are not representative for the AK-004 catchment.

Proglacial river dataset from the Akuliarusiarsuup Kuua River northern tributary, Southwest Greenland, 2008 - 2010, version 1.0

Pressing scientific questions concerning the Greenland ice sheet's climatic sensitivity, hydrology, and contributions to current and future sea level rise require hydrological datasets to resolve. While direct observations of ice sheet meltwater losses can be obtained in terrestrial rivers draining the ice sheet and from lake levels, few such datasets exist. We present a new dataset of meltwater river discharge for the vicinity of Kangerlussuaq, Southwest Greenland. The dataset contains measurements of river stage and discharge for three sites along the Akuliarusiarsuup Kuua (Watson) River's northern tributary, with 30 minute temporal resolution between June 2008 and August 2010. Additional data of water temperature, air pressure, and lake water depth and temperature are also provided. Discharge data were measured at sites with near-ideal properties for such data collection. Regardless, high water bedload and turbulent flow introduce considerable uncertainty. These were constrained and quantified using statistical techniques, thereby providing a high quality dataset from this important site. The greatest data uncertainties are associated with streambed elevation change and measurements. Large portions of stream channels deepened according to statistical tests, but poor precision of streambed depth measurements also added uncertainty. Quality checked data are freely available for scientific use as supplementary online material.

Optimal placement of piezoelectric sensor/actuators for smart structures vibration control

Smart material technology has become an area of increasing interest for the development of lighter and stronger structures that are able to incorporate actuator and sensor capabilities for collocated control. In the design of actively controlled structures, the determination of the actuator locations and the controller gains is a very important issue. For that purpose, smart material modeling, modal analysis methods, and control and optimization techniques are the most important ingredients to be taken into account. The optimization problem to be solved in this context presents two interdependent aspects. The first is related to the discrete optimal actuator location selection problem, which is solved in this paper using genetic algorithms. The second is represented by a continuous variable optimization problem, through which the control gains are determined using classical techniques. A cantilever Euler-Bernoulli beam is used to illustrate the presented methodology.

Immbolization of uricase enzyme in Langmuir and Langmuir-Blodgett films of fatty acids: Possible use as a uric acid sensor

Preserving the enzyme structure in solid films is key for producing various bioelectronic devices, including biosensors, which has normally been performed with nanostructured films that allow for control of molecular architectures. In this paper, we investigate the adsorption of uricase onto Langmuir monolayers of stearic acid (SA), and their transfer to solid supports as Langmuir Blodgett (LB) films. Structuring of the enzyme in beta-sheets was preserved in the form of 1-layer LB film, which was corroborated with a higher catalytic activity than for other uricase-containing LB film architectures where the beta-sheets structuring was not preserved. The optimized architecture was also used to detect uric acid within a range covering typical concentrations in the human blood. The approach presented here not only allows for an optimized catalytic activity toward uric acid but also permits one to explain why some film architectures exhibit a superior performance. (C) 2011 Elsevier Inc. All rights reserved.

Fine-grained Indoor Tracking by Fusing Inertial Sensor and Physical Layer Information in WLANs

Indoor positioning has become an emerging research area because of huge commercial demands for location-based services in indoor environments. Channel State Information (CSI) as fine-grained physical layer information has been recently proposed to achieve high positioning accuracy by using range based methods, e.g., trilateration. In this work, we propose to fuse the CSI-based ranging and velocity estimated from inertial sensors by an enhanced particle filter to achieve highly accurate tracking. The algorithm relies on some enhanced ranging methods and further mitigates the remaining ranging errors by a weighting technique. Additionally, we provide an efficient method to estimate the velocity based on inertial sensors. The algorithms are designed in a network-based system, which uses rather cheap commercial devices as anchor nodes. We evaluate our system in a complex environment along three different moving paths. Our proposed tracking method can achieve 1.3m for mean accuracy and 2.2m for 90% accuracy, which is more accurate and stable than pedestrian dead reckoning and range-based positioning.

Organizational concepts for the sensor-to-shooter world : the impact of real-time information on airpower targeting /

"May 1997."

Using an Infra-red sensor to measure the dynamic behaviour of N2O gas escaping through different sized holes

An anastomosis is a surgical procedure that consists of the connection of two parts of an organ and is commonly required in cases of colorectal cancer. About 80% of the patients diagnosed with this problem require surgery. The malignant tissue located on the gastrointestinal track must be resected and the most common procedure adopted is the anastomosis. Therefore, an anastomotic leak represents a significant problem and increases the duration of hospital stay, which is associated with remedial treatment and recovery, causing, as a result, a negative financial impact. A number of techniques to treat, prevent and even detect an anastomotic leakage are under investigation. However, studies show that these techniques are not always able to prevent an anastomotic leak from occurring. This paper discusses the monitoring of leakage through differently sized and differently positioned leak holes in phantom colons, using physical experiments and a Computational Fluid Dynamics package called FloWorks. © 2011 Taylor & Francis Group.

Biomass, quality traits and methane production of extensive grassland: biodiversity effects and sensor approaches

Energy policies around the world are mandating for a progressive increase in renewable energy production. Extensive grassland areas with low productivity and land use limitations have become target areas for sustainable energy production to avoid competition with food production on the limited available arable land resources and minimize further conversion of grassland into intensively managed energy cropping systems or abandonment. However, the high spatio-temporal variability in botanical composition and biochemical parameters is detrimental to reliable assessment of biomass yield and quality regarding anaerobic digestion. In an approach to assess the performance for predicting biomass using a multi-sensor combination including NIRS, ultra-sonic distance measurements and LAI-2000, biweekly sensor measurements were taken on a pure stand of reed canary grass (Phalaris aruninacea), a legume grass mixture and a diversity mixture with thirty-six species in an experimental extensive two cut management system. Different combinations of the sensor response values were used in multiple regression analysis to improve biomass predictions compared to exclusive sensors. Wavelength bands for sensor specific NDVI-type vegetation indices were selected from the hyperspectral data and evaluated for the biomass prediction as exclusive indices and in combination with LAI and ultra-sonic distance measurements. Ultrasonic sward height was the best to predict biomass in single sensor approaches (R² 0.73 – 0.76). The addition of LAI-2000 improved the prediction performance by up to 30% while NIRS barely improved the prediction performance. In an approach to evaluate broad based prediction of biochemical parameters relevant for anaerobic digestion using hyperspectral NIRS, spectroscopic measurements were taken on biomass from the Jena-Experiment plots in 2008 and 2009. Measurements were conducted on different conditions of the biomass including standing sward, hay and silage and different spectroscopic devices to simulate different preparation and measurement conditions along the process chain for biogas production. Best prediction results were acquired for all constituents at laboratory measurement conditions with dried and ground samples on a bench-top NIRS system (RPD > 3) with a coefficient of determination R2 < 0.9. The same biomass was further used in batch fermentation to analyse the impact of species richness and functional group composition on methane yields using whole crop digestion and pressfluid derived by the Integrated generation of solid Fuel and Biogas from Biomass (IFBB) procedure. Although species richness and functional group composition were largely insignificant, the presence of grasses and legumes in the mixtures were most determining factors influencing methane yields in whole crop digestion. High lignocellulose content and a high C/N ratio in grasses may have reduced the digestibility in the first cut material, excess nitrogen may have inhibited methane production in second cut legumes, while batch experiments proved superior specific methane yields of IFBB press fluids and showed that detrimental effects of the parent material were reduced by the technical treatment