The paper explores mechanisms that link trade and restructuring in countries of central and eastern Europe through a learning and industrial upgrading perspective. A theoretical model based on notions of scale (relative concentration in trade) and scope (changes in product variety) is introduced and applied, based on detailed product level data for six central and east European countries (CEECs...

This paper investigates the emergence of retail clusters on supply chains comprised of suppliers, retailers, and consumers. An agent-based model is employed to study retail location choice in a market of homogeneous goods and a market of complementary goods. On a circle comprised of discrete locales, retailers play a non-cooperative game by choosing locales to maximize profits which are impacte...

Molecular recognition between two species of Au55 clusters bearing complementary hydrogen-bonding groups provides a facile route to accomplish solution-based assembly of two-component nanoparticle aggregates.

Supply chain management clusters are geographic concentrations of three or more companies directly involved in the upstream and downstream flows of products, services, finances and/or information from a source to a customer. Clusters extend downstream to channels and customers, as well as laterally to manufacturers of complementary products. They also extend to companies in industries related b...

The observation that suicides sometimes cluster in space and/or time has led to suggestions that these clusters are caused by the social learning of suicide-related behaviours, or "copycat suicides". Point clusters are clusters of suicides localised in both time and space, and have been attributed to direct social learning from nearby individuals. Mass clusters are clusters of suicides localise...

Complementary-Label Learning (CLL) is a weakly-supervised learning problem that aims to learn multi-class classifier from only complementary labels, which indicate class an instance does not belong. Existing approaches mainly adopt the paradigm of reduction ordinary classification, applies specific transformations and surrogate losses connect CLL back classification. Those approaches, however, ...

in this study, we considered some competitive learning methods which include hard competitive learning (hcl) and soft competitive learning (scl) with/ without fixed network dimensionality for reliability analysis in microarrays. in order to have a more extensive view, and keeping in mind that competitive learning methods aim at error minimization or entropy maximization (different kinds of func...