This reflection is inspired by a discussion among leading intermedialists organized by UNISC, Brazil, fall 2021. It included contextualization and conceptualization, i.e. setting the current research within the context of the discipline’s development and the synchronic study of culture, proposing new concepts or defending old ones. The key term ‘in-between’ expresses both a trend in art, and in the self-reflecting intermedial methodology. It becomes obvious that intermedial research opens up wide to analyzing issues of social importance. In our exposition, we assess the debated concepts in terms of their analytical and educational potential in literary and cultural studies, and relate the debate to the Czech environment.
The 48-hour "Aladin" forecast model can predict significant meteorological quantities in a middle scale area. Neural networks could try to replace some statistical techniques designed to adapt a global meteorological numerical forecast model for local conditions, described with real data surface observations. They succeed commonly a cut above problem solutions with a predefined testing data set, which provides bearing inputs for a trained model. Time-series predictions of the very complex and dynamic weather system are sophisticated and not any time faithful using simple neural network models entered only some few variables of their own next-time step estimations. Predicted values of a global meteorological forecast might instead enter a neural network locally trained model, for refine it. Differential polynomial neural network is a new neural network type developed by the author; it constructs and substitutes for an unknown general sum partial differential equation of a system description, with a total sum of fractional polynomial derivative terms. This type of non-linear regression is based on trained generalized data relations, decomposed into many partial derivative specifications. The characteristics of composite differential equation solutions of this indirect type of a function description can facilitate a much greater variety of model forms than is allowed using standard soft-computing methods. This adjective derivative model type is supposed to be able to solve much more complex problems than is usual using standard neural network techniques.
In the wake of the national and political conflict in the Middle East, Arab-Jewish culture has undergone a process of marginalization and negligence, as well as a gradual descent into utter oblivion, owing to both Arab-Musim and Hebrew-Jewish-Zionist national and culural systems. Both sides, each with its own form of limited reasoning and particularistic considerations, have refused to accept the legitimacy of Arab-Jewish hybridism highlighting instead "pure" nationally, culturally, and religiously exclusive identities. The article explores the gradual demise of Arab-Jewish cultural hybridism, which, from a historical point of view, coexisted with Arab-Muslim and Arab-Christian hybridisms during some periods. Following a short era in the twentieth century during which Arab-Jewish culture flourished, especially in Egypt and Iraq, we are currently witnessing the demise of that culture. Consequently, Israeli-Arab Jews, or those seen as their offspring, currently have, or will have in the near future, three man cultural options. The first - the revival of active Jewish involvement in Arab canonical culture - is probably impossible. The second option is involvement in popular Israeli culture; this option is characterized by a strong longing for legitimacy - Jewish musicians and singers of Arab origin have accomplished a great deal in this field. The third option is participation in the activities of the canonical Hebrew culture.