Determination of the solar calibration constant for a sun-sky radiometer: proposal of an in-situ procedure

A new procedure is presented for determining in situ the solar calibration constant, i.e., the Sun-sky radiometer counts for a direct normal solar flux extrapolated to the top of the atmosphere. The method makes use of a modified version of the Langley plot based on the use of an inversion code of column-integrated aerosol size distribution, and it is ordinarily applied to calibrate Prede Sun-sky radiometers. To analyze how such an in situ method can work accurately, the technique has been applied to a five-month dataset obtained from measurements taken in Rome, Italy, by a Prede Sun-sky radiometer from 22 April to 5 November 2001. The precision of the in situ method has been estimated to within 1-2.5%, depending on the wavelength.     

Quality control of Aspergillus flavus and A. parasiticus agar and comparison with dichloran 18% glycerol agar: a collaborative study

AFPA culture medium, which is used for recognition of Aspergillus flavus and A. parasiticus, has been validated in a collaborative study including nine laboratories located in Australia, Brazil, Denmark, The Netherlands, Sweden and United Kingdom. Three freeze-dried fungal mixtures, containing A. flavus/A. parasiticus and background fungi, were produced and checked for homogeneity. The coefficients of variance were low, ranging from 0.81% to 1.09% for total fungal counts and between 2.50% and 2.72% for counts of A. flavus/A. parasiticus. The laboratories analysed the contents of two vials of each mixture on commercial A. flavus and A. parasiticus agar (AFPA), in-house-made AFPA, and on a standard media, dichloran 18% glycerol agar (DG18). Reproducibility values for counts of A. flavus/A. parasiticus indicated no differences between the commercial AFPA and the in-house-made AFPA. Variation between laboratories was low, indicating that the medium was effective in use. Reproducibility values for DG18 were higher. There were no differences in counts of A. flavus/A. parasiticus on AFPA and DG18. However, DG18 gave slightly higher total fungal counts compared to AFPA.     

Adaptive Correction of Errors in Residue Coupled MASH ΔΣ Modulators

MASH delta-sigma () modulators consist of a cascade of several lower order single-loop modulators. In an ideal cascade, the quantization error from all but the last stage are digitally canceled. The drawback with a cascaded design is the requirement of precise matching of contributions from different quantizers to cancel lower order quantization noise from intermediate delta-sigma stages. This paper presents a new, adaptive improvement to the residue coupled MASH delta sigma modulator. The adaptive corrections significantly reduce the sensitivity to analog imperfections. The result is a simple MASH delta-sigma modulator with high precision. Simulations of a 1-1 MASH circuit structure with errors and corrections are included to confirm the theory.     

Congruence in the performance of model nitrifying activated sludge plants located in Germany,Scotland and Spain

A laboratory model nitrifying activated sludge plant treating OECD synthetic sewage was designed and constructed by each of three laboratories in Germany, Scotland and Spain in order to produce a sludge inoculum for 5 rapid toxicity bioassays. The plants were run for 3 years and produced sludge for the microbially based bioassays Vibrio fischeri bioluminescence, ATP luminescence and respiration, and, nitrification and enzyme inhibition. Although the initial sludge inoculum for the plants differed, as did some of the running conditions such as temperature regime, the sludge produced within the different countries had similar characteristics with respect to sludge age, total suspended solids and volatile suspended solids. Nitrification was generally maintained over the 3-year period although there were occasions when the process was inconsistent. Nitrification recovery was afforded by reseeding with a nitrifying sludge from a local wastewater treatment works (WWTW) or imposition of starvation conditions for a period of time. The sludge produced was used to carry out toxicity testing and results compared well with those using sludge from a WWTW. Overall, the use of sludge generated in the laboratory could be used for toxicity testing negating the need to resort to the use of natural WWTW sludge, which may contain a range of toxic substances due to uncontrolled industrial and domestic inputs and an unbalanced microbial consortium.     

Biomimetic Concealing of PLGA Microspheres in a 3D Scaffold to Prevent Macrophage Uptake

Scaffolds functionalized with delivery systems for the release of growth factors is a robust strategy to enhance tissue regeneration. However, after implantation, macrophages infiltrate the scaffold, eventually initiating the degradation and clearance of the delivery systems. Herein, it is hypothesized that fully embedding the poly(d,l ‐lactide‐co‐glycolide acid) microspheres (MS) in a highly structured collagen‐based scaffold (concealing) can prevent their detection, preserving the integrity of the payload. Confocal laser microscopy reveals that non‐embedded MS are easily internalized; when concealed, J774 and bone marrow‐derived macrophages (BMDM) cannot detect them. This is further demonstrated by flow cytometry, as a tenfold decrease is found in the number of MS engulfed by the cells, suggesting that collagen can cloak the MS. This correlates with the amount of nitric oxide and tumor necrosis factor‐α produced by J774 and BMDM in response to the concealed MS, comparable to that found for non‐functionalized collagen scaffolds. Finally, the release kinetics of a reporter protein is preserved in the presence of macrophages, only when MS are concealed. The data provide detailed strategies for fabricating three dimensional (3D) biomimetic scaffolds able to conceal delivery systems and preserve the therapeutic molecules for release.     

How you move reveals who you are: understanding human behavior by analyzing trajectory data

The widespread use of mobile devices is producing a huge amount of trajectory data, making the discovery of movement patterns possible, which are crucial for understanding human behavior. Significant advances have been made with regard to knowledge discovery, but the process now needs to be extended bearing in mind the emerging field of behavior informatics. This paper describes the formalization of a semantic-enriched KDD process for supporting meaningful pattern interpretations of human behavior. Our approach is based on the integration of inductive reasoning (movement pattern discovery) and deductive reasoning (human behavior inference). We describe the implemented Athena system, which supports such a process, along with the experimental results on two different application domains related to traffic and recreation management.     

An efficient two phase approach for solving reliability–redundancy allocation problem using artificial bee colony technique

The main goal of the present paper is to present a two phase approach for solving the reliability–redundancy allocation problems (RRAP) with nonlinear resource constraints. In the first phase of the proposed approach, an algorithm based on artificial bee colony (ABC) is developed to solve the allocation problem while in the second phase an improvement of the solution as obtained by this algorithm is made. Four benchmark problems in the reliability–redundancy allocation and two reliability optimization problems have been taken to demonstrate the approach and it is shown by comparison that the solutions by the new proposed approach are better than the solutions available in the literature.     

Estimating soybean ground cover from satellite images using neural-networks models

The ground cover is a necessary parameter for agronomic and environmental applications. In Argentina, soybean (Glycine max (L.) Merill) is the most important crop; therefore it is necessary to determine its amount and configuration. In this work, neural-network (NN) models were developed to calculate soybean percentage ground cover (fractional vegetation cover, fCover) and to compare the accuracy of the estimate from Moderate-Resolution Imaging Spectroradiometer (MODIS) and Landsat satellites data. The NN design included spectral values of the red and near-infrared (NIR) bands as input variables and one neuron output, which expressed the estimated coverage. Data of fCover were acquired throughout the growing season in the central plains of Córdoba (Argentina); they were used for training and validating the networks. The results show that the NNs are an appropriate methodology for estimating the temporal evolution of soybean coverage fraction from MODIS and Landsat images, with coefficients of determination (R ²) equal to 0.90 and 0.91, respectively.