Effects of signalling tax evasion on redistribution and voting preferences: evidence from the panama papers

This paper provides empirical evidence that individuals substantially revise their stated wealth redistribution preferences after fiscal scandals. The 2016 Panama Papers scandal revealed top-income tax evasion behaviour simultaneously worldwide. The empirical investigation exploits this event as a quasi-natural experiment. I rely on two original datasets, a UK household longitudinal dataset and a survey conducted in 22 European countries. I use a difference-in-differences strategy and find that pro-redistribution statements increased between 2% and 3.3% after the scandal. Responses are heterogeneous and larger for right-wing individuals and low-income individuals. This change in wealth redistribution preferences is likely to have been translated into a slight change in votes. The results suggest an increase in stated voting intentions for the left and a decrease for the right. Complementary estimations reveal that more media coverage and more individuals involved by country increase the magnitude of the response

Genetic Algorithms for Optimal Reactive Power Compensation of a Power System with Wind Generators based on Artificial Neural Networks

In this paper, we develop a method to maintain an acceptable voltages profile and minimization of active losses of a power system including wind generators in real time. These tasks are ensured by acting on capacitor and inductance benches implemented in the consuming nodes. To solve this problem, we minimize an objective function associated to active losses under constraints imposed on the voltages and the reactive productions of the various benches. The minimization procedure was realised by the use of genetic algorithms (GA). The major disadvantage of this technique is that it requires a significant computing time thus not making it possible to deal with the problem in real time. After a training phase, a neural model has the capacity to provide a good estimation of the voltages, the reactive productions and the losses for forecast curves of the load and the wind speed, in real time

Utilisation des lichens comme bio-indicateurs de la pollution atmosphérique par le plomb, cadmium et zinc de la région de Rabat-Sale-Zemmour-Zaêr (Maroc)

Au Nord-Ouest du Maroc, la région de Rabat-Salé-Zemmour-Zaêr présente une importance socioéconomique pour le royaume. En effet, elle est sujette à deux sources de pollution; le trafic routier et les rejets des poteries. Considérant le risque de contamination métallique de l’Homme et de l’environnement, une étude a été conduite pour évaluer la pollution métallique de l’atmosphère. Elle a porté sur les bioindicateurs lichens (Xanthoria Parietina). C’est ainsi que des échantillons de thalle de Xanthoria Parietina ont été prélevés au cours de la période située entre janvier et juillet 2007 et trois éléments métalliques Plomb(Pb), Cadmium(Cd) et Zinc(Zn) ont été détectés. Les résultats de suivi spatial obtenus au niveau des quatre stations étudiées (Kamra, Centre ville, Oulja et Allal Behraoui) ont révélé des concentrations moyennes mensuelles dépassant les normes requises à l’exception de la station de Allal Behraoui. Les résultats de suivi temporel obtenus au niveau des lichens montrent que la variation saisonnière atmosphérique des métaux est très marquée avec des teneurs plus élevées en hiver et plus basses en été.Mots-clés : métaux lourds, lichens, plomb, cadmium, zinc, Rabat, salé, Zemmour, Zaêr, Maroc

Qualité physicochimique et bactériologique de trois stations thermales dans les régions de Fès, Maroc

Les sources thermales au Maroc constituent une richesse inestimable et sont fréquemment exploitées par la population pour différents usages. Cette dernière peut être exposée à des risques de contamination par des germes pathogènes dans les stations thermales mal entretenues. C'est dans ce cadre qu'une étude portant sur la qualité physicochimique et bactériologique de trois sources situées près de la ville de Fès : Sidi Harazem, Moulay Yaâcoub et Ain Allah a été réalisée. Les prélèvements d'eau effectués mensuellement entre Octobre 2012 et Mars 2013 dans les trois stations et à différents points, ont été analysés selon des protocoles standardisés conformément aux normes. Les résultats ont montré que les paramètres physico-chimiques des eaux des trois stations prélevées au niveau des fontaines et du réservoir répondent aux normes marocaines en vigueur. Les analyses bactériologiques ont montré l’absence des germes pathogènes dans les eaux de fontaine des trois stations étudiées. Les eaux de piscine de la station Ain Allah ont présenté, une forte contamination par la flore mésophile et les indicateurs de pollution fécale (coliformes totaux, coliformes fécaux, Escherichia coli et les streptocoques fécaux) par rapport aux eaux de piscine de la station Moulay Yaâcoub qui présentent des densités très faibles. Cette charge bactérienne est liée essentiellement à la fréquentation de cette station par nombre important de baigneurs durant cette saison ainsi qu’à la température qui favorise la croissance des micro-organismes. L’utilisation de ces eaux pour la baignade pourrait être à l’origine de maladies transmises par les eaux de baignade. Ces piscines doivent donc être soumises à un contrôle régulier de la charge et de la nature de la flore microbienne de leurs eaux.Mots-clés: sidi harazem, moulay Yaâcoub, ain allah, physico-chimie, bactériologie, fès, Maroc. Physicochemical and bacteriological quality of three spas in Fez region (Morocco)Hot springs in Morocco are an invaluable wealth and are frequently used by the population for different purposes. The latter may be exposed to the risk of contamination by pathogens in poorly maintained spas. It is in this context, a study of the physico-chemical and bacteriological quality of three springs near Fez city: Sidi Harazem, Moulay Yaâcoub and Ain Allah was performed. Water samples collected monthly between October 2012 and March 2013 in the three stations and at different points were analyzed according to standardized and normalized protocols. The results showed that the physico-chemical parameters of the three station’s waters collected from fountain and reservoir meet Moroccan standards (NM 03.07.001/2006). Bacteriological analysis showed the absence of pathogens in the fountain’s water of the three studied stations. The swimming pool’s water of Ain Allah station presented a strong contamination by mesophilic flora and by faecal pollution indicators (total coliforms, fecal coliforms, Escherichia coli and faecal streptococci) comparing to the water of Moulay Yacoub station swimming pool which exhibit very low bacterial densities. This bacterial density is mainly related to the large number of bathers in this station during this season and also to the temperature that promotes the microorganism’sgrowth. The use of these waters for swimming could be the cause of diseases and illness transmitted by bathing waters. These swimming pools must be subject to regular monitoring of the density and the nature oftheir water’s microbial flora.Keywords: sidi harazem, moulay yaâcoub, ain allah, physico-chemical, bacteriology, fez, Morocco

The factor structure of the mood disorder questionnaire in Tunisian patients

Background: The Mood Disorder Questionnaire (MDQ) is a frequently used screening tool for the early detection of Bipolar Disorder (BD), which is often unrecognized or misdiagnosed at its onset. In this study, data from Tunisia has been used to evaluate the psychometric properties of the Arabic MDQ. Methods: The sample included 151 patients with a current major depressive episode. The Arabic adapted version of the Structured Clinical Interview for DSM-IV-TR was used to formulate a diagnosis, yielding 62 patients with BD and 89 with unipolar Major Depressive Disorder (MDD). Principal component analysis with parallel analysis was used to establish the spontaneous distribution of the 13 core items of the MDQ. Confirmatory Factor Analysis (CFA) was used to check the available factor models. Receiver Operating Characteristic (ROC) analysis was used to assess the capacity of the MDQ to distinguish patients with BD from those with MDD. Results: Cronbach’s α in the sample was 0.80 (95%CI: 0.75 to 0.85). Ordinal α was 0.88. Parallel analysis suggested two main components, which explained 59% of variance in the data. CFA found a good fit for the existing unidimensional, the two-factor, and the three-factor models. ROC analysis showed that at a threshold of 7, the MDQ was able to distinguish patients with BD from those with MDD with extraordinary negative predictive value (0.92) and a positive diagnostic likelihood ratio of 3.8. Conclusion: The Arabic version of the MDQ showed good measurement properties in terms of reliability, factorial validity and discriminative properties

Accuracy of the Arabic HCL - 32 and MDQ in detecting patients with bipolar disorder

Background: Studies about the two most used and validated instruments for the early detection of Bipolar Disorder (BD), the 32 - item Hypomania Checklist (HCL - 32) and the Mood Disorder Questionnaire (MDQ), are scarce in non-Western countries. This study aimed to explore the reliability, factor structure, and criterion validity of their Arabic versions in a sample of Tunisian patients diagnosed with mood disorders. Methods: The sample included 59 patients with BD, 86 with unipolar Major Depressive Disorder (MDD) and 281 controls. Confirmatory factor analysis was applied to show that a single global score was an appropriate summary measure of the screeners in the sample. Receiver Operating Characteristic analysis was used to assess the capacity of the translated screeners to distinguish patients with BD from those with MDD and controls. Results: Reliability was good for both tools in all samples. The bifactor implementation of the most reported two-factor model had the best fit for both screeners. Both were able to distinguish patients diagnosed with BD from putatively healthy controls, and equally able to distinguish patients diagnosed with BD from patients with MDD. Conclusion: Both screeners work best in excluding the presence of BD in patients with MDD, which is an advantage in deciding whether or not to prescribe an antidepressant

Kinetics of fragmentation-annihilation processes

We investigate the kinetics of systems in which particles of one species undergo binary fragmentation and pair annihilation. In the latter, nonlinear process, fragments react at collision to produce an inert species, causing loss of mass. We analyse these systems in the reaction-limited regime by solving a continuous model within the mean-field approximation. The rate of fragmentation, for a particle of mass $x$ to break into fragments of masses $y$ and $x-y$, has the form $x^{\lambda-1}$ ($\lambda>0$), and the annihilation rate is constant and independent of the masses of the reactants. We find that the asymptotic regime is characterized by the annihilation of small-mass clusters. The results are compared with those for a model with linear mass-loss (i.e.\ with a sink). We also study more complex models, in which the processes of fragmentation and annihilation are controlled by mutually-reacting catalysts. Both pair- and linear-annihilation are considered. Depending on the specific model and initial densities of the catalysts, the time-decay of the cluster-density can now be very unconventional and even non-universal. The interplay between the intervening processes and the existence of a scaling regime are determined by the asymptotic behaviour of the average-mass and of the mass-density, which may either decay indefinitely or tend to a constant value. We discuss further developments of this class of models and their potential applications.Comment: 16 pages(LaTeX), submitted to Phys. Rev.

Predicting gene function using hierarchical multi-label decision tree ensembles

<p>Abstract</p> <p>Background</p> <p><it>S. cerevisiae</it>, <it>A. thaliana </it>and <it>M. musculus </it>are well-studied organisms in biology and the sequencing of their genomes was completed many years ago. It is still a challenge, however, to develop methods that assign biological functions to the ORFs in these genomes automatically. Different machine learning methods have been proposed to this end, but it remains unclear which method is to be preferred in terms of predictive performance, efficiency and usability.</p> <p>Results</p> <p>We study the use of decision tree based models for predicting the multiple functions of ORFs. First, we describe an algorithm for learning hierarchical multi-label decision trees. These can simultaneously predict all the functions of an ORF, while respecting a given hierarchy of gene functions (such as FunCat or GO). We present new results obtained with this algorithm, showing that the trees found by it exhibit clearly better predictive performance than the trees found by previously described methods. Nevertheless, the predictive performance of individual trees is lower than that of some recently proposed statistical learning methods. We show that ensembles of such trees are more accurate than single trees and are competitive with state-of-the-art statistical learning and functional linkage methods. Moreover, the ensemble method is computationally efficient and easy to use.</p> <p>Conclusions</p> <p>Our results suggest that decision tree based methods are a state-of-the-art, efficient and easy-to-use approach to ORF function prediction.</p