Caffeine as an indicator for the quantification of untreated wastewater in karst systems

Contamination from untreated wastewater leakage and related bacterial contamination poses a threat to drinking water quality. However, a quantification of the magnitude of leakage is difficult. The objective of this work is to provide a highly sensitive methodology for the estimation of the mass of untreated wastewater entering karst aquifers with rapid recharge. For this purpose a balance approach is adapted. It is based on the mass flow of caffeine in spring water, the load of caffeine in untreated wastewater and the daily water consumption per person in a spring catchment area. Caffeine is a source-specific indicator for wastewater, consumed and discharged in quantities allowing detection in a karst spring. The methodology was applied to estimate the amount of leaking and infiltrating wastewater to a well investigated karst aquifer on a daily basis. The calculated mean volume of untreated wastewater entering the aquifer was found to be 2.2 ± 0.5 m³ d⁻¹ (undiluted wastewater). It corresponds to approximately 0.4% of the total amount of wastewater within the spring catchment.     

Power consumption benchmarking for reconfigurable platforms

Software defined radios (SDR) wideband mobile terminals must be capable of data processing while consuming low power and keeping the design and manufacturing costs as low as possible. SDR can combine high performance signal processing and flexibility, but power efficiency of SDR nodes is an issue that needs to be addressed. Analysis of power consumption for various target technologies is challenging, since each technology typically contains its own benchmarking tools and thus, results are not comparable. In this paper, we illustrate how the GroundHog2009 benchmark suite, designed to be platform independent, can be used to evaluate power dissipation of four modern FPGAs and one microcontroller. We also introduce a generic RTL library for the GroundHog2009 design cases and test bench infra-structure to make the toolset usage easy. In addition, we show that power can be saved by using clock management, available on one of the FGPA-boards. The power savings range from 38 to 1,150?%.     

World‐record Cu(In,Ga)Se2‐based thin‐film sub‐module with 17.4% efficiency

We report a new certified world‐record efficiency for thin‐film Cu(In,Ga)Se₂‐based photovoltaic sub‐modules of 17.4% (aperture area). The record efficiency of the 16 cm², monolithically integrated, sub‐module has been independently confirmed by Fraunhofer ISE. The record device is the result of extensive co‐optimization of all processing steps. During the optimization process, strong focus has been put on the scalability of processes to cost‐effective mass production, as reflected, for example, in Cu(In,Ga)Se₂ deposition time and substrate temperature. Device manufacturing as well as results of electrical and material characterization is discussed. Copyright © 2012 John Wiley & Sons, Ltd.     

Spin cast self-assembled monolayer field effect transistors

Top-contact self-assembled monolayer field-effect transistors (SAMFETs) were fabricated through both spin-coating and solution assembly of a semiconducting phosphonic acid-based molecule (11-(5?-butyl-[2,2′;5′,2″;5″,2?;5?,2?]quinquethiophen-5-yl)undecylphosphonic acid) (BQT-PA). The field-effect mobilities of both spin-cast and solution assembled SAMFETs were 1.1-8.0 × 10⁻⁶ cm² V⁻¹ s⁻¹ for a wide range of channel lengths (between 12 and 80 μm). The molecular monolayers were characterized by atomic force microscopy (AFM), attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR), and near edge X-ray absorption fine structure (NEXAFS) spectroscopy. It was found that the BQT-PA monolayer films exhibit dense surface coverage, bidentate binding, and tilt angles of ∼32° and ∼44° for the thiophene rings and alkyl chain, respectively. These results indicate that rapid throughput of fabricating SAMFETs is possible even by spin-coating.     

Insect Egg Deposition Induces Indirect Defense and Epicuticular Wax Changes in Arabidopsis thaliana

Egg deposition by the Large Cabbage White butterfly Pieris brassicae on Brussels sprouts plants induces indirect defense by changing the leaf surface, which arrests the egg parasitoid Trichogramma brassicae. Previous studies revealed that this indirect defense response is elicited by benzyl cyanide (BC), which is present in the female accessory reproductive gland (ARG) secretion and is released to the leaf during egg deposition. Here, we aimed (1) to elucidate whether P. brassicae eggs induce parasitoid-arresting leaf surface changes in another Brassicacean plant, i.e., Arabidopsis thaliana, and, if so, (2) to chemically characterize the egg-induced leaf surface changes. Egg deposition by P. brassicae on A. thaliana leaves had similar effects to egg deposition on Brussels sprouts with respect to the following: (a) Egg deposition induced leaf surface changes that arrested T. brassicae egg parasitoids. (b) Application of ARG secretion of mated female butterflies or of BC to leaves had the same inductive effects as egg deposition. Based on these results, we conducted GC-MS analysis of leaf surface compounds from egg- or ARG-induced A. thaliana leaves. We found significant quantitative differences in epicuticular waxes compared to control leaves. A discriminant analysis separated surface extracts of egg-laden, ARG-treated, untreated control and Ringer solution-treated control leaves according to their quantitative chemical composition. Quantities of the fatty acid tetratriacontanoic acid (C34) were significantly higher in extracts of leaf surfaces arresting the parasitoids (egg-laden or ARG-treated) than in respective controls. In contrast, the level of tetracosanoic acid (C24) was lower in extracts of egg-laden leaves compared to controls. Our study shows that insect egg deposition on a plant can significantly affect the quantitative leaf epicuticular wax composition. The ecological relevance of this finding is discussed with respect to its impact on the behavior of egg parasitoids.     

Using multiple genetic variants as instrumental variables for modifiable risk factors

Mendelian randomisation analyses use genetic variants as instrumental variables (IVs) to estimate causal effects of modifiable risk factors on disease outcomes. Genetic variants typically explain a small proportion of the variability in risk factors; hence Mendelian randomisation analyses can require large sample sizes. However, an increasing number of genetic variants have been found to be robustly associated with disease-related outcomes in genome-wide association studies. Use of multiple instruments can improve the precision of IV estimates, and also permit examination of underlying IV assumptions. We discuss the use of multiple genetic variants in Mendelian randomisation analyses with continuous outcome variables where all relationships are assumed to be linear. We describe possible violations of IV assumptions, and how multiple instrument analyses can be used to identify them. We present an example using four adiposity-associated genetic variants as IVs for the causal effect of fat mass on bone density, using data on 5509 children enrolled in the ALSPAC birth cohort study. We also use simulation studies to examine the effect of different sets of IVs on precision and bias. When each instrument independently explains variability in the risk factor, use of multiple instruments increases the precision of IV estimates. However, inclusion of weak instruments could increase finite sample bias. Missing data on multiple genetic variants can diminish the available sample size, compared with single instrument analyses. In simulations with additive genotype-risk factor effects, IV estimates using a weighted allele score had similar properties to estimates using multiple instruments. Under the correct conditions, multiple instrument analyses are a promising approach for Mendelian randomisation studies. Further research is required into multiple imputation methods to address missing data issues in IV estimation.