Assessing the tilt of the solar magnetic field axis through Faraday rotation observations

Context: Faraday rotation measurements of extragalactic radio sources during coronal occultation allow assessment of both the electron density distribution and the three-dimensional magnetic field topology in the outer solar corona. Aims: We simulate the three-dimensional structure of both the coronal magnetic field and the electron density distribution in order to reproduce the excess Faraday rotation measures (RMs) of the occulted radio sources observed during solar activity minimum. In particular, we infer the tilt of the solar magnetic axis with respect to the rotation axis. Methods: We compare the output of the model with Very Large Array (VLA) radio polarimetric measurements of a sample of extragalactic sources observed in May 1997. Information on the magnetic field geometry can be retrieved by fine-tuning the set of model free parameters that best describe the observations. Results: We find that predicted and observed Faraday rotation measures are in excellent agreement, thus supporting the model. Our best-fitting model yields a tilt angle $\theta_{RB}=3.3^{\circ}$ of the solar magnetic axis with respect to the solar rotation axis around Carrington Rotation 1923. This result is consistent with analogous but independent estimates computed from the expansion coefficients of the photospheric field observed at the Wilcox Solar Observatory (WSO).Comment: 8 pages, 5 figures, accepted for publication in A&

Three-dimensional reconstruction of CME-driven shock-streamer interaction from radio and EUV observations: a different take on the diagnostics of coronal magnetic fields

On 2014 October 30, a band-splitted type II radio burst associated with a coronal mass ejection (CME) observed by the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamic Observatory (SDO) occurred over the southeast limb of the Sun. The fast expansion in all directions of the plasma front acted as a piston and drove a spherical fast shock ahead of it, whose outward progression was traced by simultaneous images obtained with the Nan\c{c}ay Radioheliograph (NRH). The geometry of the CME/shock event was recovered through 3D modeling, given the absence of concomitant stereoscopic observations, and assuming that the band-splitted type II burst was emitted at the intersection of the shock surface with two adjacent low-Alfven speed coronal streamers. From the derived spatiotemporal evolution of the standoff distance between shock and CME leading edge, we were finally able to infer the magnetic field strength $B$ in the inner corona. A simple radial profile of the form $B(r) = (12.6 \pm 2.5) r^{-4}$ nicely fits our results, together with previous estimates, in the range $r = 1.1-2.0$ solar radii.Comment: Accepted for publication in Astronomy & Astrophysics Letter

Trends on the Harmonization of Contract Law in Africa

The article examines the different initiatives of the harmonization of contract law in the African contex

Fractal geometry-based image analysis of grapevine leaves using the box counting algorithm

An image analysis method based on the box counting algorithm was evaluated for its potential to characterize grapevine leaves. Although vine leaves lack the self-similarity of the theoretical fractals, leaves are candidates for characterization using fractal analysis because of their highly complex structure. The results showed for 11 Sangiovese-related genotypes fractal dimensions significantly being different except for (1) Prugnolo acerbo, Prugnolo dolce and Prugnolo medio and (2) Chiantino, Brunelletto and Morellino di Scansano, which have shown a high similarity in agreement with previous studies. Fractal dimension calculated for leaves of Sangiovese R10 grown in very different environments did not show any statistically significant modification revealing that fractal dimension can be considered environment-independent. Consequently, fractal dimension could be used as a descriptive, scale-invariant, condensed, morphological parameter in ampelographic research. The role of the fractal dimension as an additional morphological parameter in future ampelographic classification schemes of grapevine leaves is discussed

The integration of informal business law in the OHADA framework. Methodological reflections

OHADA represents today a successful example of legal integration that offers a modern and reliable legal environment regarding business law in those countries that have joined it. However, such a modern integrated system of business law appears to be unsuited to the informal business sector that still represents a vital segment of the economy in most of the African countries. The paper discusses the attempts that have been made to integrate the informal business sector in the OHADA framework, trying to understand the reasons why they have been substantially unsuccessful and suggests a possible way forward to make such integration possible

Elliptic Fourier Analysis (EFA) and Artificial Neural Networks (ANNs) for the identification of grapevine (Vitis vinifera L.) genotypes

The potential application of the Elliptic Fourier Analysis (EFA) for the objective quantitative description of leaf morphology, combined with the use of a Back-propagation Neural Network (BPNN) for data modelling, was evaluated to characterize and identifiy 12 Sangiovese-related accessions (Vitis vinifera L.). The results enable us to distinguish, with considerable certainty, between 10 accessions. Cluster analysis revealed the existence of a uniform group for the Prugnolo (acerbo, medio and dolce) ecotypes showing a high degree of relatedness. Among all accessions only the so-called Casentino ecotype significantly diverged from all the others, indicating probably a different origin. The application of EFA coupled with the use of artificial neural networks opens interesting prospects for the characterization of varieties, allowing to study differences and/or relationships which can not be detected by standard ampelographic systems

Discrimination of grapevine (Vitis vinifera L.) leaf shape by fractal spectrum

A technique was developed (1) to digitise grapevine leaves, (2) to split the images obtained in the three components of the RGB (red, green and blue) colour system, obtain the fractal spectrum for each colour component of the leaf and (3) to calculate 15 different fractal parameters. The system, consisting of a scanning device, a personal computer and the code written in the C language, was then tested to characterize and identify 12 Sangiovese-related grapevine accessions. The results enabled us to distinguish between all accessions with a better discrimination than that obtained in previous studies with molecular markers or elliptic Fourier analysis. More, all the fractal parameters calculated for leaves of Sangiovese R10 grown in very different environments did not show any significant modification, revealing that fractal features can be considered environment-independent. The fractal analysis approach proposed, on the basis of the results obtained, gives the opportunity to verify the characters of distinction, uniformity and stability (DUS) requested by the Union for the Protection of Plant Varieties (UPOV) before plant breeders rights are granted

The New African Law: Beyond the Difference Between Common Law and Civil Law

The article analyzes the developments of African law in a comparative perspective, considering how the contraposition between the two main legal traditions affects such development

Clustering of grapevine (Vitis vinifera L.) genotypes with Kohonen neural networks

Self-organizing maps generated by Kohonen neural networks provide a method to transform multidimensional problems common in ampelography into lower dimensional problems. In this study the clustering efficiency of Kohonen neural networks was evaluated to characterize and identify 10 Sangiovese-related and 10 "coloured" (fruit gives intense red colour to the wine) grapevine accessions, on the basis of the elliptic Fourier coefficients of the leaves. The non-supervised learning algorithm used allowed apriori classification of the accessions. The results enabled us to distinguish between 16 accessions and to denote two pairs of synonyms, To obtain quantitative information regarding relationships among these accessions, Kohonen neural networks were trained with different numbers of neurons in the Kohonen output layer permitting the graphical representation of the similarity by construction of a dendrogram. In agreement with previous studies based on molecular markers and neural network technology, a high similarity was found for the ecotypes (1) Prugnolo acerbo, Prugnolo dolce and Prugnolo medio and (2) Brunelletto and Prugnolo gentile. Among the Sangiovese-related accessions the so-called Casentino ecotype diverged from all the others, probably indicating a different origin. Producing easily comprehensible low-dimensional maps, the Kohonen neural networks approach proposed here allows to study complex ampelographic data elucidating relationships that can not be detected by traditional data analysis tools