The communication networks (mobile phone networks, social media platforms) produce digital traces from their usages. This type of information help to understand and analyze the human mobility in very accurate way. By these analyzes over cities, it can give powerful data on daily citizen activities, urban planners have in that way, relevant indications for decision making on design and development. As well as, the Call detail Records (CDRs) provides valuable spatiotemporal data at the level of citywide or even nationwide. The CDRs could be analyzed to extract the life patterns and individuals mobility in an observed urban area and during ephemeral events. Whereas, their analysis gives conceptual views about human density and mobility patterns. In this study, the mobile phone traces concern an ephemeral event called Armada in Rouen city. However, important densities of individuals are analyzed and are represented to extract the life patterns by classifying the most active regions during observed period in this urban area. Then, the collective mobility patterns are investigated in aggregated urban mobility patterns via extracting the universal mobility law (power-law distribution). This investigation explores the characteristics of human mobility patterns, and model them mathematically depending on substantial parameters, that are the inter-event time, traveled distances (displacements), and the radius of gyration. The main purpose of this study is to determine the general pattern law of the population. And, its contribution is the resulting outcomes, which are revealed and visualized in both static and dynamic perspectives. They can be capitalized as guidelines to explore the urban pulse and life patterns. The numerical simulation results endorse the previous investigations. Hence, they found that the real system patterns almost follow an exponential distribution. Additionally, the experiments classified the mobility patterns into major classes as general, work, and off days. Keywords : Complex systems, urban, mobility, CDRs, mobile phone, spatio-temporal, network, radius of gyration, individual trajectory, city pulse, simulation, power-law distribution.
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Non-steroidal anti-inflammatory drugs (NSAIDs) contain free –COOH which thought to be responsible for the GI irritation associated with all traditional NSAIDs. The esterification of this group is one of an approach to ultimate aim for reduce the gastric irritation; so in this study we synthesized and preliminarily evaluated new ester compounds as new analogues with expected selectivity toward COX-2 enzyme. Synthetic procedures have been successfully developed for the generation of the target compounds (III a and b). The synthetic approach involved multi-steps procedures which include: Synthesis of 4-hydroxy benzene sulphonamide ( I b ), synthesis of Naproxen and Ibuprofen acyl chloride and then reacting them with 4-hydroxy benzene sulphon
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In this study Candida speices was diagnosed in 26 swab samples from patients with denture stomatitis , investigates the antagonism activity of Lactobacillus was investigated against the yeast of Candida albicans in vitro.Results revealed that The inhibition effect of Lactic Acid Bacteria against C.albicans was examined in solid medium, L.plantarum gave higher inhibition average 11mm followed by L.acidophillus with average 9 mm and, L.fermentum , L.casei with averages 7 mm. Whereas the filtrates, the highest inhibition zone were 20 and 16 mm by L. plantarum and L.acidophillus, respectively.
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The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of
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