Improving OPERA radar data for nowcasting

Póster presentado en: 3rd European Nowcasting Conference, celebrada en la sede central de AEMET en Madrid del 24 al 26 de abril de 2019

Adaptive stochastic Gauss-Newton method with optical Monte Carlo for quantitative photoacoustic tomography

SIGNIFICANCE: The image reconstruction problem in quantitative photoacoustic tomography (QPAT) is an ill-posed inverse problem. Monte Carlo method for light transport can be utilized in solving this image reconstruction problem. AIM: The aim was to develop an adaptive image reconstruction method where the number of photon packets in Monte Carlo simulation is varied to achieve a sufficient accuracy with reduced computational burden. APPROACH: The image reconstruction problem was formulated as a minimization problem. An adaptive stochastic Gauss-Newton (A-SGN) method combined with Monte Carlo method for light transport was developed. In the algorithm, the number of photon packets used on Gauss-Newton (GN) iteration was varied utilizing a so-called norm test. RESULTS: The approach was evaluated with numerical simulations. With the proposed approach, the number of photon packets needed for solving the inverse problem was significantly smaller than in a conventional approach where the number of photon packets was fixed for each GN iteration. CONCLUSIONS: The A-SGN method with a norm test can be utilized in QPAT to provide accurate and computationally efficient solutions

Image reconstruction in quantitative photoacoustic tomography using adaptive optical Monte Carlo

In quantitative photoacoustic tomography (QPAT), distributions of optical parameters inside the target are reconstructed from photoacoustic images. In this work, we utilize the Monte Carlo (MC) method for light transport in the image reconstruction of QPAT. Modeling light transport accurately with the MC requires simulating a large number of photon packets, which can be computationally expensive. On the other hand, too low number of photon packets results in a high level of stochastic noise, which can lead to significant errors in reconstructed images. In this work, we use an adaptive approach, where the number of simulated photon packets is adjusted during an iterative image reconstruction. It is based on a norm test where the expected relative error of the minimization direction is controlled. The adaptive approach automatically determines the number of simulated photon packets to provide sufficiently accurate light transport modeling without unnecessary computational burden. The presented approach is studied with two-dimensional simulations

Effect of peracetic acid on geosmin and 2-methylisoborneol levels in recirculating aquaculture system raising rainbow trout Oncorhynchus mykiss

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Changes in the metabolome of Picea balfouriana embryogenic tissues that were linked to different levels of 6-BAP by gas chromatography-mass spectrometry approach

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Jensen-Shannon Complexity and Permutation Entropy Analysis of Geomagnetic Auroral Currents

In this study we determine whether auroral westward currents can be characterized by low-dimensional chaotic attractors through the use of the complexity-entropy methodology developed by Rosso et al. (2007, https:// doi.org/10.1103/PhysRevLett.99.154102) and based on the permutation entropy developed by Bandt and Pompe (2002, https://doi.org/10.1103/PhysRevLett.88.174102) . Our results indicate that geomagnetic auroral indices are indistinguishable from stochastic processes from time scales ranging from a few minutes to 10 hr and for embedded dimensions d <8. Our results are inconsistent with earlier studies of Baker et al. (1990, https://doi.org/10.1029/GL017i001p00041), Pavlos et al. (1992), D. Roberts et al. (1991, https://doi.org/10.1029/91GL00021), D. A. Roberts (1991, https://doLorg/10.1029/91JA01088), and Vassiliadis et al. (1990, https://doi.org/10.1029/GL017i011 p01841, 1991, https://doi.org/10.1029/91GL01378) indicating that auroral geomagnetic indices could be reduced to low-dimensional systems with chaotic dynamics.Peer reviewe

Gold nanoparticles : calixarene complexation in a mixed calixarene-alkanethiol monolayer

Peer reviewe

Differences in branch characteristics of Scots pine (Pinus sylvestris L.) genetic entries grown at different spacing

• We studied the differences in branch characteristics along the stems of six different genetic entries of 20 year old Scots pines (Pinus sylvestris L.) grown at different spacing (current stand density range 2000–4000 trees ha−1) in central Finland. Furthermore, we studied the phenotypic correlations between yield, wood density traits and branch characteristics. All the genetic entries had Kanerva pine (plus tree S1101) as a father tree, whereas the mother tree represented Finnish plus trees from southern, central and northern Finland. • Spacing affected all yield traits, wood density and living branch characteristics such as relative average branch diameter and relative cumulative branch area (p < 0.05). As a comparison, genetic entry affected height, while origin group (southern, central and northern ones) affected most of the studied traits. Regardless of spacing, the northern origin had, on average, the largest stem diameter and highest wood density, while the central one was the tallest one. Furthermore, average branch diameter along the stem was affected by branch age, origin group and spacing, while average branch angle was affected by branch age and genetic entry (p < 0.05). • In general the average branch size could be decreased especially in lower tree canopy by denser spacing during the early phase of the rotation, but only at the expense of tree growth. Correspondingly differences between origins are mainly related to their differences in stem growth

Energy conversion at the Earth's magnetopause using single and multispacecraft methods

We present a small statistical data set, where we investigate energy conversion at the magnetopause using Cluster measurements of magnetopause crossings. The Cluster observations of magnetic field, plasma velocity, current density and magnetopause orientation are needed to infer the energy conversion at the magnetopause. These parameters can be inferred either from accurate multispacecraft methods, or by using single-spacecraft methods. Our final aim is a large statistical study, for which only single-spacecraft methods can be applied. The Cluster mission provides an opportunity to examine and validate single-spacecraft methods against the multispacecraft methods. For single-spacecraft methods, we use the Generic Residue Analysis (GRA) and a standard one-dimensional current density method using magnetic field measurements. For multispacecraft methods, we use triangulation (Constant Velocity Approach - CVA) and the curlometer technique. We find that in some cases the single-spacecraft methods yield a different sign for the energy conversion than compared to the multispacecraft methods. These sign ambiguities arise from the orientation of the magnetopause, choosing the interval to be analyzed, large normal current and time offset of the current density inferred from the two methods. By using the Finnish Meteorological Institute global MHD simulation GUMICS-4, we are able to determine which sign is likely to be correct, introducing an opportunity to correct the ambiguous energy conversion values. After correcting the few ambiguous cases, we find that the energy conversion estimated from single-spacecraft methods is generally lower by 70% compared to the multispacecraft methods.Peer reviewe