A detailed biostratigraphic study of four sections (El Kantara, Menaa, Tighanimine and El Gaâga) in the Campanian–Maastrichtian of the Aures Basin in Algeria allows the identification of 109 ostracod species belonging to 50 genera. From a biochronostratigraphic point of view, none of the identified ostracod assemblages are typically restricted to the Campanian or to the Maastrichtian, but rather characterize a range covering the Campanian–Maastrichtian. As regards the paleobiogeography, the presence of species in common between Algeria and other countries or regions enables us to compile four maps showing the distribution of two provinces that developed during the Santonian-Paleocene, i) the South-West and South Tethyan Margins Province, including North Africa, the Middle East and Arabian Peninsula, and ii) the East Atlantic Margin Province, bordering West and Central-West Africa. We can also recognize relationships between the different regions making up these provinces, which remained under more or less arid, subtropical to tropical climates, with ostracods migrating according to the directions of ocean currents during the Late Cretaceous. The dispersal of the ostracods reflects marine communication between these provinces and India, the southern USA and Jamaica, Brazil and Europe.

  This paper aims to address the assessment the similarity between documents or pieces of documents. For this purpose we have developed CASISS (CAlculation of SImilarity of Semi-Structured documents) method to quantify how two given texts are similar. The method can be employed in wide area of applications including content reuse detection which is a hot and challenging topic. It can be also used to increase the accuracy of the information retrieval process by taking into account not only the presence of query terms in the given document (Content Only search — CO) but also the topology (position continuity) of these terms (based on Content And Structure Search — CAS). Tracking the origin of the information in social media, copy right management, plagiarism detection, social media mining and monitoring, digital forensic are among other applications require tools such as CASISS to measure, with a high accuracy, the content overlap between two documents. CASISS identify elements of semi-structured documents using elements descriptors. Each semi-structured document is pre-processed before the extraction of a set of elements descriptors, which characterize the content of the elements.  

Despite the significant advances achieved these recent last years in terms of technologies widespread use in medical education, clinical reasoning learning (CRL) remains an extremely hard task in which there are still many gray areas that should be enlightened to better understand it. Furthermore, while CRL is basically a collaborative task implying the participation of many students and tutors working simultaneously on a same case, it should be considered from a social perspective. The authors followed then a collaborative-based learning approach, which consists in designing a shared workspace to support collaboration and enable social clinical knowledge acquisition. They started with a deep analysis of the CRL process in order to understand the usual way under which students learn together and then, highlight the vital collaborative learning tasks that need to be supported. The resulting designed model allowed us to shift towards Collaborative CRL (CCRL).

In collaborative clinical learning field, several recent pertinent studies showed that gathering learners with their tutor still insufficient to improve students' learning quality and knowledge acquisition. Consequently, focusing attention on professional skills within a collaboration environment seems to be the most appropriate way to reach the wished learning objectives, particularly in a complex specialty such as medical diagnosis learning. In this paper, we firstly introduce the concept of medical diagnosis from cognitive studies view that have been performed in the field of medical education. Then, we will discuss our shared web environment designed to support distance diagnosis learning, which aims to promote knowledge coconstruction and collaboration between learner