Embedded Sensor System for Early Pathology Detection in Building Construction

Structure pathology detection is an important security task in building construction, which is performed by an operator by looking manually for damages on the materials. This activity could be dangerous if the structure is hidden or difficult to reach. On the other hand, embedded devices and wireless sensor networks (WSN) are becoming popular and cheap, enabling the design of an alternative pathology detection system to monitor structures based on these technologies. This article introduces a ZigBee WSN system, intending to be autonomous, easy to use and with low power consumption. Its functional parts are fully discussed with diagrams, as well as the protocol used to collect samples from sensor nodes. Finally, several tests focused on range and power consumption of our prototype are shown, analysing whether the results obtained were as expected or not

Enzymatic synthesis of natural (+)-aristolochene from a non-natural substrate

The sesquiterpene cyclase aristolochene synthase from Penicillium roquefortii (PR-AS) has evolved to catalyse with high specificity (92%) the conversion of farnesyl diphosphate (FDP) to the bicyclic hydrocarbon (+)-aristolochene, the natural precursor of several fungal toxins. Here we report that PR-AS converts the unnatural FDP isomer 7-methylene farnesyl diphosphate to (+)-aristolochene via the intermediate 7-methylene germacrene A. Within the confined space of the enzyme's active site, PR-AS stabilises the reactive conformers of germacrene A and 7-methylene germacrene A, respectively, which are protonated by the same active site acid (most likely HOPPi) to yield the shared natural bicyclic intermediate eudesmane cation, from which (+)-aristolochene is then generated

Convergence of simple adaptive Galerkin schemes based on h − h/2 error estimators

We discuss several adaptive mesh-refinement strategies based on (h − h/2)-error estimation. This class of adaptivemethods is particularly popular in practise since it is problem independent and requires virtually no implementational overhead. We prove that, under the saturation assumption, these adaptive algorithms are convergent. Our framework applies not only to finite element methods, but also yields a first convergence proof for adaptive boundary element schemes. For a finite element model problem, we extend the proposed adaptive scheme and prove convergence even if the saturation assumption fails to hold in general

How nitrogen and phosphorus availability change water use efficiency in a Mediterranean savanna ecosystem

Nutrient availability, especially of nitrogen (N) and phosphorus (P), is of major importance for every organism and at a larger scale for ecosystem functioning and productivity. Changes in nutrient availability and potential stoichiometric imbalance due to anthropogenic nitrogen deposition might lead to nutrient deficiency or alter ecosystem functioning in various ways. In this study, we present 6 years (2014–2020) of flux-, plant-, and remote sensing data from a large-scale nutrient manipulation experiment conducted in a Mediterranean savanna-type ecosystem with an emphasis on the effects of N and P treatments on ecosystem-scale water-use efficiency (WUE) and related mechanisms. Two plots were fertilized with N (NT, 16.9 Ha) and N + P (NPT, 21.5 Ha), and a third unfertilized plot served as a control (CT). Fertilization had a strong impact on leaf nutrient stoichiometry only within the herbaceous layer with increased leaf N in both fertilized treatments and increased leaf P in NPT. Following fertilization, WUE in NT and NPT increased during the peak of growing season. While gross primary productivity similarly increased in NT and NPT, transpiration and surface conductance increased more in NT than in NPT. The results show that the NPT plot with higher nutrient availability, but more balanced N:P leaf stoichiometry had the highest WUE. On average, higher N availability resulted in a 40% increased leaf area index (LAI) in both fertilized treatments in the spring. Increased LAI reduced aerodynamic conductance and thus evaporation at both fertilized plots in the spring. Despite reduced evaporation, annual evapotranspiration increased by 10% (48.6 ± 28.3 kg H2O m−2), in the NT plot, while NPT remained similar to CT (−1%, −6.7 ± 12.2 kgH2O m−2). Potential causes for increased transpiration at NT could be increased root biomass and thus higher water uptake or rhizosphere priming to increase P-mobilization through microbes. The annual net ecosystem exchange shifted from a carbon source in CT (75.0 ± 20.6 gC m−2) to carbon-neutral in both fertilized treatments [−7.0 ± 18.5 gC m−2 (NT) 0.4 ± 22.6 gC m−2 (NPT)]. Our results show, that the N:P stoichiometric imbalance, resulting from N addition (without P), increases the WUE less than the addition of N + P, due to the strong increase in transpiration at NT, which indicates the importance of a balanced N and P content for WUE

Multiple-constraint inversion of SCOPE. Evaluating the potential of GPP and SIF for the retrieval of plant functional traits

The most recent efforts to provide remote sensing (RS) estimates of plant function rely on the combination of Radiative Transfer Models (RTM) and Soil-Vegetation-Atmosphere Transfer (SVAT) models, such as the Soil-Canopy Observation Photosynthesis and Energy fluxes (SCOPE) model. In this work we used ground spectroradiometric and chamber-based CO2 flux measurements in a nutrient manipulated Mediterranean grassland in order to: 1) develop a multiple-constraint inversion approach of SCOPE able to retrieve vegetation biochemical, structural as well as key functional traits, such as chlorophyll concentration (Cab), leaf area index (LAI), maximum carboxylation rate (Vcmax) and the Ball-Berry sensitivity parameter (m); and 2) compare the potential of the of gross primary production (GPP) and sun-induced fluorescence (SIF), together with up-welling Thermal Infrared (TIR) radiance and optical reflectance factors (RF), to estimate such parameters. The performance of the proposed inversion method as well as of the different sets of constraints was assessed with contemporary measurements of water and heat fluxes and leaf nitrogen content, using pattern-oriented model evaluation. The multiple-constraint inversion approach proposed together with the combination of optical RF and diel GPP and TIR data provided reliable estimates of parameters, and improved predicted water and heat fluxes. The addition of SIF to this scheme slightly improved the estimation of m. Parameter estimates were coherent with the variability imposed by the fertilization and the seasonality of the grassland. Results revealed that fertilization had an impact on Vcmax, while no significant differences were found for m. The combination of RF, SIF and diel TIR data weakly constrained functional traits. Approaches not including GPP failed to estimate LAI; however GPP overestimated Cab in the dry period. These problems might be related to the presence of high fractions of senescent leaves in the grassland. The proposed inversion approach together with pattern-oriented model evaluation open new perspectives for the retrieval of plant functional traits relevant for land surface models, and can be utilized at various research sites where hyperspectral remote sensing imagery and eddy covariance flux measurements are simultaneously taken

Association of Serum Ferritin Levels Before Start of Conditioning With Mortality After alloSCT - A Prospective, Non-interventional Study of the EBMT Transplant Complications Working Party

Elevated serum ferritin levels occur due to iron overload or during inflammation and macrophage activation. A correlation of high serum ferritin levels with increased mortality after alloSCT has been suggested by several retrospective analyses as well as by two smaller prospective studies. This prospective multicentric study aimed to study the association of ferritin serum levels before start of conditioning with alloSCT outcome. Patients with acute leukemia, lymphoma or MDS receiving a matched sibling alloSCT for the first time were considered for inclusion, regardless of conditioning. A comparison of outcomes between patients with high and low ferritin level was performed using univariate analysis and multivariate analysis using cause-specific Cox model. Twenty centers reported data on 298 alloSCT recipients. The ferritin cut off point was determined at 1500 mu g/l (median of measured ferritin levels). In alloSCT recipients with ferritin levels above cut off measured before the start of conditioning, overall survival (HR = 2.5, CI = 1.5-4.1, p = 0.0005) and progression-free survival (HR = 2.4, CI = 1.6-3.8, p <0.0001) were inferior. Excess mortality in the high ferritin group was due to both higher relapse incidence (HR = 2.2, CI = 1.2-3.8, p = 0.007) and increased non-relapse mortality (NRM) (HR = 3.1, CI = 1.5-6.4, p = 0.002). NRM was driven by significantly higher infection-related mortality in the high ferritin group (HR = 3.9, CI = 1.6-9.7, p = 0.003). Acute and chronic GVHD incidence or severity were not associated to serum ferritin levels. We conclude that ferritin levels can serve as routine laboratory biomarker for mortality risk assessment before alloSCT.Peer reviewe

Wind and turbulence relationship with NO2 in an urban environment: a fine-scale observational analysis

It is well known that meteorology plays an important role in the diurnal evolution of pollutants, especially those variables related to atmospheric dispersion. Most studies typically relate the concentration of some pollutants with wind speed from conventional anemometers; however, the use of turbulence variables is less common, in part because the needed instruments are not so typical in standard air-quality stations. In this work, we compare the wind-NO2 relationship with the turbulence-NO2 one using observational data from two field campaigns developed in Madrid (winter and summer). The turbulence data comes from two sonic anemometers deployed at different locations: one close to the street and the other at the top of a nearby tall building. The results indicate that the turbulent variables correlate better with the pollutant concentration than the wind speed when using data from the street sonic, while the contrary is found when using the terrace sonic. These data are also used to perform a fine-scale analysis of the turbulent diffusion-NO2 behaviour during a very-stable period in winter, when the turbulence typically shows a decrease in the evening transition, causing the highestNO2 concentrations. Conversely, under these conditions, the formation of thermally-driven winds is also favoured later in the night, which favours the pollutant dispersion and cleaning of the air. The important role of these dynamical processes on the NO2 evolution highlights the importance of the correct understanding of small-scale atmospheric processes to understand their relationship with the concentration of pollutants