Subsoil <Superscript>15</Superscript>N-N<Subscript>2</Subscript>O Concentrations in a Sandy Soil Profile After Application of <Superscript>15</Superscript>N-fertilizer

Studies on emissions of nitrous oxide (N₂O) from agricultural soils mostly focus on fluxes between the soil and the atmosphere or are limited to the atmosphere in the topsoil. However, in soils with shallow water tables, significant N₂O formation may occur closer to the groundwater. The aims of this study were (i) to determine the importance of subsoil N₂O formation in a sandy soil; and (ii) to obtain a quantitative insight in the contribution of subsoil N₂O to the overall losses of N₂O to the environment. We applied ¹⁵N labeled fertilizer at a rate of 5.22 kg ¹⁵N ha⁻¹; 50% as Ca(NO₃)₂ and 50% as NH₄Cl, on a mesic typic Haplaquod seeded with potatoes (Solanum tuberosum L.), and traced soil N₂O concentrations and fluxes over a one-year period. Throughout the year, total N₂O and the amount of ¹⁵N recovered in soil N₂O were highest in the subsoil, with a maximum concentration at 48 cm depth in mid-February of 19900 μl m⁻³ and 24 μg ¹⁵N m⁻³, respectively. The maximum concentration coincided with the highest water-filled pore space of 71%. The cumulative flux of N₂O was 446 g N₂O-N ha⁻¹, the recovery of ¹⁵N in this flux was 0.06%. During the summer, maximum fluxes followed high soil N₂O concentrations. During winter, no such relation was found. We concluded that the formation of N₂O was the highest in the subsoil, largely controlled by water-filled pore space rather than NO₃⁻ concentration or temperature. Although high subsoil N₂O concentrations did not lead to high surface fluxes of N₂O in the winter, artificial draining may lead to high indirect N₂O emissions through supersaturated drainage water.     

Tight Bounds for Distributed Minimum-Weight Spanning Tree Verification

This paper introduces the notion of distributed verification without preprocessing. It focuses on the Minimum-weight Spanning Tree (MST) verification problem and establishes tight upper and lower bounds for the time and message complexities of this problem. Specifically, we provide an MST verification algorithm that achieves simultaneously $\tilde{O}(m)$ messages and $\tilde{O}(\sqrt{n} + D)$ time, where m is the number of edges in the given graph G, n is the number of nodes, and D is G’s diameter. On the other hand, we show that any MST verification algorithm must send $\tilde{\varOmega}(m)$ messages and incur $\tilde{\varOmega}(\sqrt{n} + D)$ time in worst case. Our upper bound result appears to indicate that the verification of an MST may be easier than its construction, since for MST construction, both lower bounds of $\tilde{\varOmega}(m)$ messages and $\tilde{\varOmega}(\sqrt{n} + D)$ time hold, but at the moment there is no known distributed algorithm that constructs an MST and achieves simultaneously $\tilde{O}(m)$ messages and $\tilde{O}(\sqrt{n} + D)$ time. Specifically, the best known time-optimal algorithm (using ${\tilde{O}}(\sqrt {n} + D)$ time) requires O(m+n ^3/2) messages, and the best known message-optimal algorithm (using ${\tilde{O}}(m)$ messages) requires O(n) time. On the other hand, our lower bound results indicate that the verification of an MST is not significantly easier than its construction.     

Medical image segmentation with transform and moment based features and incremental supervised neural network

In this study, a novel incremental supervised neural network (ISNN) is proposed for the segmentation of medical images. Performance of the ISNN is investigated for tissue segmentation in medical images obtained from various imaging modalities. Two feature extraction methods based on transform and moments are comparatively investigated to segment the tissues in medical images. Two-dimensional (2D) continuous wavelet transform (CWT) and the moments of the gray-level histogram (MGH) are computed in order to form the feature vectors of ultrasound (US) bladder and phantom images, X-ray computerized tomography (CT) and magnetic resonance (MR) head images. In the 2D-CWT method, feature vectors are formed by the intensity of one pixel of each wavelet-plane of different energy bands. The MGH represents the tissues within the sub-windows by using the spatial variation of image intensities. In this study, the ISNN and Grow and Learn (GAL) network are employed for the segmentation task. It is observed that the ISNN has significantly eliminated the disadvantages of the GAL network in the segmentation of the medical images.     

Physics-guided machine learning from simulated data with different physical parameters

Knowledge and Information Systems - Physics-based models are widely used to study dynamical systems in a variety of scientific and engineering problems. However, these models are necessarily...     

Clustering MIT–BIH arrhythmias with Ant Colony Optimization using time domain and PCA compressed wavelet coefficients

In this paper, Ant Colony Optimization (ACO) based clustering analysis of ECG arrhythmias taken from the MIT–BIH Arrhythmia Database is proposed. Both time domain and discrete wavelet transform (DWT) based frequency domain features are used in the analysis. Since the number of wavelet coefficients are huge amount as compared to the time domain parameters, Principal Component Analysis (PCA) based compression is applied on them in order to decrease their number to the number of time domain features. Then, the reduced numbers of frequency parameters are combined with the time domain features, in order to get the total feature sets. Different types of feature sets are tried and the classification results are compared. These are: time domain feature set, frequency domain feature set and the mixture of them. A neural network algorithm is developed in parallel to verify and measure the ACO classifier's success. Moreover, linear discriminant analysis (LDA) is used to show the effect of clustering on the system's results. The method is tested with MIT–BIH database to classify normal beats and five different critical and having vital importance arrhythmia types. Chosen six classes are normal sinus rhythm, premature ventricular contraction (PVC), atrial premature contraction (APC), right bundle branch block (RBBB), ventricular fusion (F) and fusion (f). Comparison results indicate that the mixture feature set gave a better success for the classification.     

Evaluation and comparison of satellite-based rainfall products in Burkina Faso,West Africa

The performance of seven operational high-resolution satellite-based rainfall products – Africa Rainfall Estimate Climatology (ARC 2.0), Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), African Rainfall Estimation (RFE 2.0), Tropical Applications of Meteorology using SATellite (TAMSAT), African Rainfall Climatology and Time-series (TARCAT), and Tropical Rainfall Measuring Mission (TRMM) daily and monthly estimates – was investigated for Burkina Faso. These were compared to ground data for 2001–2014 on a point-to-pixel basis at daily to annual time steps. Continuous statistics was used to assess their performance in estimating and reproducing rainfall amounts, and categorical statistics to evaluate rain detection capabilities. The north–south gradient of rainfall was captured by all products, which generally detected heavy rainfall events, but showed low correlation for rainfall amounts. At daily scale they performed poorly. As the time step increased, the performance improved. All (except TARCAT) provided excellent scores for Bias and Nash–Sutcliffe Efficiency coefficients, and overestimated rainfall amounts at the annual scale. RFE performed the best, whereas TARCAT was the weakest. Choice of product depends on the specific application: ARC, RFE, and TARCAT for drought monitoring, and PERSIANN, CHIRPS, and TRMM daily for flood monitoring in Burkina Faso.     

2‐D/3‐D displays based on switchable lenticulars

Abstract— An attractive concept for 3‐D displays is the one based on LCDs equipped with lenticular lenses. This enables autostereoscopic multiview 3‐D displays without a loss in brightness. A general issue in multiview 3‐D displays is their relatively low spatial resolution because the pixels are divided among the different views. To overcome this problem, we have developed switchable displays, using liquid‐crystal (LC) filled switchable lenticulars. In this way, it is possible to have a high‐brightness 3‐D display capable of fully exploiting the native 2‐D resolution of the underlying LCD. The feasibility of LC‐filled switchable lenticulars was shown in several applications. For applications in which it is advantageous to be able to display 3‐D and 2‐D content simultaneously, a 42‐in. locally switchable prototype having a matrix electrode structure was developed. These displays were realized using cylindrically shaped lenticular lenses in contact with LC. An alternative for these are lenticulars based on gradient‐index (GRIN) LC lenses. Preliminary results for such switchable GRIN lenses are presented as well.     

Improvement of luminance and luminous efficacy in PDPs

Abstract— The dependence of PDP luminance and efficacy on the input power was investigated for several Xe‐Ne gas mixtures. The input power was varied in two ways: namely, by changing the dielectric‐layer capacitance (thickness) and by changing the sustain voltage. A distinctly different behavior was found; for increasing capacitance the efficacy decreases markedly, whereas for increasing sustain voltage the efficacy increases. A design window comprising the combination of a high Xe concentration and a high sustain voltage was suggested. In this window, a high luminance and a high efficacy are concurrent. A 4‐in. test panel with 10% Xe in Ne has been realized showing a white luminance of 2040 cd/m² and an efficacy of 2.3 lm/W for continuous sustaining at 50 kHz with a sustain voltage of 225 V.     

High‐Xe‐content high‐efficacy PDPs

Abstract— The trade‐off between PDP efficacy improvement and driving voltages was investigated for several design factors. It was found that for a proper combination of an increased Xe content, cell design, and the use of a TiO₂ layer combined with “non‐saturating” phosphors, a large increase in both efficacy and luminance can be realized at moderately increased drive voltages. In a 4‐in. color test panel, a white efficacy of 5 lm/W and a luminance of 5000 cd/m² was obtained for sustaining at 260 V in addressed condition.     

Prediction of the asphaltene deposition profile along a wellbore during natural production from a reservoir

The potential problem of asphaltene deposition during oil production has motivated both academics and industries to predict the asphaltene deposit profile in wellbores and pipelines. In this work, asphaltene deposition profile along an oil field well with the severe problem of asphaltene deposition was predicted. To do this, a comprehensive simulator for modeling of flow parameters such as pressure, temperature, and composition for a multiphase flow of oil, gas, and asphaltene from the reservoir to the surface was developed and coupled with the deposition model. By applying the simulator to an oil field well, it has been found that 60–70% of the total asphaltene thickness formed after 1 month of production, indicating that the problem of asphaltene deposition is bound to the initial stage of wellbore life. Moreover, the simulator was able to predict the accumulated asphaltene thickness and the time of wellbore plugging properly. This prediction is highly crucial if it is aimed to control the well performance and to optimize the productivity.