Fièvre des marécages : invincible et mutuelle.

Le paludisme est une érythrocytopathie fébrile et hémolysante, c’est une endémie parasitaire majeure provoquée par un hématozoaire du genre plasmodium. Il sévit principalement dans les zones tropicales et intertropicales du globe. L’OMS déclare qu’il s’y produit chaque année entre 270 et 480 millions de cas cliniques, et entre 1,5 et 2,7 millions de décès ; un enfant de moins de 5 ans sur 20 meurt de paludisme, ainsi le diagnostic de paludisme doit être évoqué devant tout ictère fébrile au retour d’une zone d’endémie. Le diagnostic positif qui varie d’un accès palustre simple à un neuro-paludisme, est confirmé par la présence, à n’importe quel stade, de l’hématozoaire dans le sang. Il est objectivé par le frottis sanguin et la goutte épaisse, technique de concentration de référence, remplacée par de nouvelles méthodes telles que la détection d’antigènes palustres par le TDR, le QBC malaria test, Ainsi que la détection des acides nucléiques par les techniques d’amplification génique. La prophylaxie reste la meilleure technique de lutte contre la paludisme, cette prophylaxie comprend deux volets : La chimioprophylaxie qui dépend de la zone, de la saison et du sujet, et la lutte antivectorielle qui consiste en plusieurs mesures tels que : la pulvérisation intradomiciliare, les moustiquaires imprégnées d’insecticides , les répulsifs, les vêtements imprégnés d'insecticides, la gestion des gites larvaires et la technique de l’insecte stérile. Sous traitement antipaludique, la guérison peut être obtenue sans séquelles, cependant , au cours de l’infestation par le plasmodium falciparum, le pronostic vital est mis en jeu du fait de la multiplication des schizogonies au niveau des capillaires de l’organisme dans un tableau d’hyperthermie

Evaluation and selection of clustering methods using a hybrid group MCDM

Due to the lack of objective measures, the evaluation and prioritization of clustering methods is inherently challenging. Since their evaluation generally involves numerous criteria, it can be designed as a multiple criteria decision making (MCDM) problem and using multiple data sets, the problem can be formulated as a group MCDM modeling. In this paper, a MCDM-based framework is proposed to evaluate and rank a number of clustering methods. The proposed approach employs three group MCDM algorithms and a Borda count method which leads to a comprehensive, robust framework capable of evaluating and ranking multiple clustering models on manifold data sets (cases). Moreover, we introduce a hybrid data clustering algorithm which combines a particle swarm optimization (PSO) algorithm with a K-means clustering algorithm. Finally, a clustering comparison with regard to both external and internal evaluation indicators is another contribution of this paper. Six clustering methods are compared based on five evaluation measures. The results of comparative experiments on ten data sets indicate the effectiveness of the proposed hybrid clustering method. More importantly, the experimental results vividly demonstrate the effectiveness of the group MCDM-based evaluation on clustering model selection.Web of Science138art. no. UNSP 11281

Facile N9-Alkylation of Xanthine Derivatives and Their Use as Precursors for N-Heterocyclic Carbene Complexes

The xanthine-derivatives 1,3,7-trimethylxanthine, 1,3-dimethyl-7-benzylxanthine and 1,3-dimethyl-7-(4-chlorobenzyl)xanthine are readily ethylated at N9 using the cheap alkylating agents ethyl tosylate or diethyl sulfate. The resulting xanthinium tosylate or ethyl sulfate salts can be converted into the corresponding PF6− and chloride salts. The reaction of these xanthinium salts with silver(I) oxide results in the formation of different silver(I) carbene-complexes. In the presence of ammonia, ammine complexes [Ag(NHC)(NH3)]PF6 are formed, whilst with Et2NH, the bis(carbene) salts [Ag(NHC)2]PF6 were isolated. Using the xanthinium chloride salts neutral silver(I) carbenes [Ag(NHC)Cl] were prepared. These silver complexes were used in a variety of transmetallation reactions to give the corresponding gold(I), ruthenium(II) as well as rhodium(I) and rhodium(III) complexes. The compounds were characterized by various spectroscopic methods as well as X-ray diffraction

Proposing Of A New Soft Computing-Based Model To Predict Peak Particle Velocity Induced By Blasting

Estimation of ground vibration induced by blasting operations is an important task to control the safety issues at the surface mines and civil projects. By reviewing the previous studies, some empirical and soft computing models have been proposed to estimate blast-induced ground vibrations. The main goal of this research is to propose a new predictive model in the field of ground vibration estimation. For this aim, the group method of data handling (GMDH) model which is a type of neural network, is proposed with respect to input parameters including the stemming length, powder factor, burden to spacing ratio, distance from the blast-face, blast-hole depth and maximum charge per delay. Also, the peak particle velocity, as the most common descriptor for evaluating the ground vibration, was selected as the output. The required datasets were collected from a quarry in Penang, Malaysia, using 102 blasting operations. Several criteria such as root mean square error (RMSE) and coefficient of determination (R2) were utilized to determine the reliability of the GMDH. Based on the obtained results, the GMDH forecasting technique with R2 of 0.911 and RMSE of 0.889 can be presented as a powerful technique in predicting the blast-induced ground vibration

COVID-19 and cancer risk arising from ionizing radiation exposure through CT scans: a cross-sectional study

Abstract Background The surge in the utilization of CT scans for COVID-19 diagnosis and monitoring during the pandemic is undeniable. This increase has brought to the forefront concerns about the potential long-term health consequences, especially radiation-induced cancer risk. This study aimed to quantify the potential cancer risk associated with CT scans performed for COVID-19 detection. Methods In this cross-sectional study data from a total of 561 patients, who were referred to the radiology center at Imam Hossein Hospital in Shahroud, was collected. CT scan reports were categorized into three groups based on the radiologist’s interpretation. The BEIR VII model was employed to estimate the risk of radiation-induced cancer. Results Among the 561 patients, 299 (53.3%) were males and the average age of the patients was 49.61 ± 18.73 years. Of the CT scans, 408 (72.7%) were reported as normal. The average age of patients with normal, abnormal, and potentially abnormal CT scans was 47.57 ± 19.06, 54.80 ± 16.70, and 58.14 ± 16.60 years, respectively (p-value < 0.001). The average effective dose was 1.89 ± 0.21 mSv, with 1.76 ± 0.11 mSv for males and 2.05 ± 0.29 mSv for females (p-value < 0.001). The average risk of lung cancer was 3.84 ± 1.19 and 9.73 ± 3.27 cases per 100,000 patients for males and females, respectively. The average LAR for all cancer types was 10.30 ± 6.03 cases per 100,000 patients. Conclusions This study highlights the critical issue of increased CT scan usage for COVID-19 diagnosis and the potential long-term consequences, especially the risk of cancer incidence. Healthcare policies should be prepared to address this potential rise in cancer incidence and the utilization of CT scans should be restricted to cases where laboratory tests are not readily available or when clinical symptoms are severe