Same or different?Abstract relational concept use in juvenile bamboo sharks and Malawi cichlids

Sorting objects and events into categories and concepts is an important cognitive prerequisite that spares an individual the learning of every object or situation encountered in its daily life.Accordingly,specific items are classified in general groups that allow fast responses to novel situations.The present study assessed whether bamboo sharks Chiloscyllium griseum and Malawi cichlids Pseudotropheus zebra can distinguish sets of stimuli(each stimulus consisting of two abstract,geometric objects)that meet two conceptual preconditions,i.e.,(1)"sameness"versus"difference"and(2)a certain spatial arrangement of both objects.In two alternative forced choice experiments,individuals were first trained to choose two different,vertically arranged objects from two different but horizontally arranged ones.Pair discriminations were followed by extensive transfer test experiments.Transfer tests using stimuli consisting of(a)black and gray circles and(b)squares with novel geometric patterns provided conflicting information with respect to the learnt rule"choose two different,vertically arranged objects",thereby investigating(1)the individuals'ability to transfer previously gained knowledge to novel stimuli and(2)the abstract relational concept(s)or rule(s)applied to categorize these novel objects.Present results suggest that the level of processing and usage of both abstract concepts differed considerably between bamboo sharks and Malawi cichlids.Bamboo sharks seemed to combine both concepts-although not with equal but hierarchical prominence-pointing to advanced cognitive capabilities.Conversely,Malawi cichlids had difficulties in discriminating between symbols and failed to apply the acquired training knowledge on new sets of geometric and,in particular,gray-level transfer stimuli.

An Advanced Analysis of Cloud Computing Concepts Based on the Computer Science Ontology

Our primary research hypothesis stands on a simple idea:The evolution of top-rated publications on a particular theme depends heavily on the progress and maturity of related topics.And this even when there are no clear relations or some concepts appear to cease to exist and leave place for newer ones starting many years ago.We implemented our model based on Computer Science Ontology(CSO)and analyzed 44 years of publications.Then we derived the most important concepts related to Cloud Computing(CC)from the scientific collection offered by Clarivate Analytics.Our methodology includes data extraction using advanced web crawling techniques,data preparation,statistical data analysis,and graphical representations.We obtained related concepts after aggregating the scores using the Jaccard coefficient and CSO Ontology.Our article reveals the contribution of Cloud Computing topics in research papers in leading scientific journals and the relationships between the field of Cloud Computing and the interdependent subdivisions identified in the broader framework of Computer Science.

CONFLICT ANALYSIS APPROACHES FOR INVESTIGATING ATTITUDES AND MISPERCEPTIONS IN THE WAR OF 1812

Formal systems engineering approaches to modeling misperceptions and attitudes are employed within the framework of the graph model for conflict resolution to systematically study the War of 1812 between the United States of America and Great Britain in order to provide enhanced insights into the causes of the war. More specifically, relational definitions for preferences, movements and stability concepts are defined for describing the attitudes and associated behavior of decision makers involved in a conflict. To capture misperceptions of decision makers in the War of 1812, attitudes are studied within the structure of a hypergame. Combining attitudes and misperceptions within the paradigm of the graph model furnishes the flexible analytical tool which demonstrates that misunderstanding of attitudes by Great Britain and the United States may have contributed to the outbreak of this nasty war.