Regression Trees and Random forest based feature selection for malaria risk exposure prediction

This paper deals with prediction of anopheles number, the main vector of malaria risk, using environmental and climate variables. The variables selection is based on an automatic machine learning method using regression trees, and random forests combined with stratified two levels cross validation. The minimum threshold of variables importance is accessed using the quadratic distance of variables importance while the optimal subset of selected variables is used to perform predictions. Finally the results revealed to be qualitatively better, at the selection, the prediction , and the CPU time point of view than those obtained by GLM-Lasso method

Brainy Africans to Fortress Europe: For Money or Colonial Vestiges?

Economic reasons along with cultural affinities and the existence of networks have been the main determinants explaining migration flows between home and host countries. This paper reconsiders these approaches combined with the gravity model and empirically tests the hypothesis that ex-colonial links can still play an important role in the emigration decision. We employ a general linear mixed model, and apply it to the case of skilled, educated and talented Africans, who migrate to Fortress Europe over the period of 1990 to 2001. While we find some differences in the exodus of skilled Africans by sub-regions, the magnitude of the colonial vestige in Africa is a significant determinant of emigration flows. Overall, Portugal is preferred to the UK which is preferred more than Belgium, Germany and Italy. Brainy Africans are, however, indifferent between the UK, France and Spain as a destination country. Established immigrant networks and higher standards of living with job opportunities in the host country are also very important drivers of the emigration of brainy Africans to the European ex-colonial powers.skilled migration, Africa, colonization, networks, economic reasons

Surviving the Turbulence Is Not Enough: Can Côte d'Ivoire Flourish Again?

Côte d'Ivoire is the world’s largest producer and exporter of cocoa beans, it accounts for 40% of the WAEMU's output, and 11% of its population are immigrant workers. Any political instability in the country will not only affect the domestic economy, but it will also affect the international trading markets. In addition, it will affect the West Africa region through trading of goods, through migration and the financial and banking sectors. With the new President sworn in on May 21, 2011, the political crisis is officially over. Real national reconciliation, however, will take much longer to happen. Serious economic issues need to be addressed, the country has high public debt, and its small and medium enterprises – the backbone of the economy – are severely hit. Côte d'Ivoire lags behind other developing countries in its preparedness and economic performance towards the Knowledge Economy, its educational sector is underperforming and powerless in producing a competitive labor force. Can the new President heal wounds and make the country flourish again?immigra, regional economics, Africa, economic development, education, national budget, public economics, government policy and regulation, international relations, conflict resolution, macroeconomic policy, trade, international migration, remittances

Le catholicisme québécois sur le divan. Les essais du psychanalyste André Lussier dans Cité Libre

Soulevant la question des rapports entre catholicisme et psychanalyse, cet article propose d’explorer la contribution d’André Lussier à la revue Cité libre. Dans quelques essais percutants parus au tournant des années 1960, cet ancien élève d’Anna Freud et pionnier de la psychanalyse à Montréal observe le malaise qui afflige le catholicisme québécois. Le diagnostic sévère qu’il formule à l’endroit de la culture catholique met en relief deux grandes pathologies : un rapport clerc-laïc névrotique qui prend la forme d’une dynamique parent-enfant et une économie déséquilibrée des rapports de genre. Par la radicalité de leur contenu, les propos d’André Lussier sont annonciateurs de l’effritement, dans l’espace idéologique québécois, du mouvement réformiste catholique.This article raises the question of the relations between Catholicism and psychoanalysis by proposing to explore the contribution of André Lussier to the journal Cité libre. In a few striking essays published at the turn of the 1960s, this former student of Anna Freud and pioneer of psychoanalysis in Montreal observes the malaise afflicting Quebec Catholicism. The severe diagnosis he makes concerning Catholic culture highlights two significant pathologies: a neurotic clergy-layperson relationship in the form of a parent-child dynamic, and an unbalanced economy of gender relations. The radical nature of their content makes the writings of André Lussier harbingers of the disintegration, in Quebec cultural ideology, of the Catholic reformist movement

Inhibition of the Aminopeptidase from \u3cem\u3eAeromonas proteolytica\u3c/em\u3e by l-leucinethiol: Kinetic and Spectroscopic Characterization of a Slow, Tight-binding Inhibitor–enzyme Complex

The peptide inhibitor l-leucinethiol (LeuSH) was found to be a potent, slow-binding inhibitor of the aminopeptidase from Aeromonas proteolytica (AAP). The overall potency (KI*) of LeuSH was 7 nM while the corresponding alcohol l-leucinol (LeuOH) was a simple competitive inhibitor of much lower potency (KI=17 μM). These data suggest that the free thiol is likely involved in the formation of the E·I and E·I* complexes, presumably providing a metal ligand. In order to probe the nature of the interaction of LeuSH and LeuOH with the dinuclear active site of AAP, we have recorded both the electronic absorption and EPR spectra of [CoCo(AAP)], [CoZn(AAP)], and [ZnCo(AAP)] in the presence of both inhibitors. In the presence of LeuSH, all three Co(II)-substituted AAP enzymes exhibited an absorption band centered at 295 nm, characteristic of a S→Co(II) ligand-metal charge-transfer band. In addition, absorption spectra recorded in the 450 to 700 nm region all showed changes characteristic of LeuSH and LeuOH interacting with both metal ions. EPR spectra recorded at high temperature (19 K) and low power (2.5 mW) indicated that, in a given enzyme molecule, LeuSH interacts weakly with one of the metal ions in the dinuclear site and that the crystallographically identified μ-OH(H) bridge, which has been shown to mediate electronic interaction of the Co(II) ions, is likely broken upon binding LeuSH. EPR spectra of [CoCo(AAP)]-LeuSH, [ZnCo(AAP)]-LeuSH, and [Co_(AAP)]-LeuSH were also recorded at lower temperature (3.5–4.0 K) and high microwave power (50–553 mW). These signals were unusual and appeared to contain, in addition to the incompletely saturated contributions from the signals characterized at 19 K, a very sharp feature at geff∼6.5 that is characteristic of thiolate-Co(II) interactions. Combination of the electronic absorption and EPR data indicates that LeuSH perturbs the electronic structure of both metal ions in the dinuclear active site of AAP. Since the spin–spin interaction seen in resting [CoCo(AAP)] is abolished upon the addition of LeuSH, it is unlikely that a μ-S(R) bridge is established

Lasso based feature selection for malaria risk exposure prediction

In life sciences, the experts generally use empirical knowledge to recode variables, choose interactions and perform selection by classical approach. The aim of this work is to perform automatic learning algorithm for variables selection which can lead to know if experts can be help in they decision or simply replaced by the machine and improve they knowledge and results. The Lasso method can detect the optimal subset of variables for estimation and prediction under some conditions. In this paper, we propose a novel approach which uses automatically all variables available and all interactions. By a double cross-validation combine with Lasso, we select a best subset of variables and with GLM through a simple cross-validation perform predictions. The algorithm assures the stability and the the consistency of estimators.Comment: in Petra Perner. Machine Learning and Data Mining in Pattern Recognition, Jul 2015, Hamburg, Germany. Ibai publishing, 2015, Machine Learning and Data Mining in Pattern Recognition (proceedings of 11th International Conference, MLDM 2015

African Leaders: Their Education Abroad and FDI Flows

Leaders are critical to a country’s success. They can influence domestic policy via specific measures that they enforce, and they can also influence international public opinion towards their country. Foreign Direct Investments are also essential for a country’s economic growth. Our hypothesis is that foreign-educated leaders attract more FDI to their country. Our rationale is that education obtained abroad encompasses a whole slew of factors that can make a difference in FDI flows when this foreign-educated individual becomes a leader. We test this hypothesis empirically with a unique dataset that we constructed from several sources, including the Library of Congress and the World Bank. Our analysis of 40 African countries employs the robust technique of conditional quantile regression. Our results reveal that foreign education is a significant determinant of FDI inflows, beyond other standard characteristics. While intuitive, this result does not necessarily indicate sheepskin effects or superior human capital obtained abroad. Rather, it indicates the powerful role of the social capital, networks, and connections that these leaders built while they were abroad that they in turn mobilize and utilize when they become leaders.FDI, leaders' educational level, return migration, Africa