Feature-based Groundwater Hydrograph Clustering Using Unsupervised Self-Organizing Map-Ensembles

Hydrograph clustering helps to identify dynamic patterns within aquifers systems, an important foundation of characterizing groundwater systems and their influences, which is necessary to effectively manage groundwater resources. We develope an unsupervised modeling approach to characterize and cluster hydrographs on regional scale according to their dynamics. We apply feature-based clustering to improve the exploitation of heterogeneous datasets, explore the usefulness of existing features and propose new features specifically useful to describe groundwater hydrographs. The clustering itself is based on a powerful combination of Self-Organizing Maps with a modified DS2L-Algorithm, which automatically derives the cluster number but also allows to influence the level of detail of the clustering. We further develop a framework that combines these methods with ensemble modeling, internal cluster validation indices, resampling and consensus voting to finally obtain a robust clustering result and remove arbitrariness from the feature selection process. Further we propose a measure to sort hydrographs within clusters, useful for both interpretability and visualization. We test the framework with weekly data from the Upper Rhine Graben System, using more than 1800 hydrographs from a period of 30 years (1986-2016). The results show that our approach is adaptively capable of identifying homogeneous groups of hydrograph dynamics. The resulting clusters show both spatially known and unknown patterns, some of which correspond clearly to external controlling factors, such as intensive groundwater management in the northern part of the test area. This framework is easily transferable to other regions and, by adapting the describing features, also to other time series-clustering applications.

     

The evolution of the international business field: a scientometric investigation of articles published in its premier journal

Macro-environmental trends such as technological changes, declining trade and investment barriers, and globalizing forces impacting both markets and production worldwide point to the heightened importance of international business (IB) and the relevance of IB research today. Despite this, a leading scholar has expressed concerns that the IB research agenda could be ‘running out of steam’ (Buckley, Journal of International Business Studies 33(2):365–373, 2002), prompting on-going introspection within the IB field. We contribute to this debate by investigating the evolution of the IB field through a scientometric examination of articles published in its premier journal, the Journal of International Business Studies (JIBS) from 1970 until 2008. We introduce a new analytical tool, Leximancer, to the fields of international business and scientometry. We show an evolution from an initial and extended emphasis on macro-environmental issues to a more recent focus on micro-economic, firm-level ones with the multinational enterprise (MNE) as an organizational form enduring throughout the entire period. We observe a field that has established a justifiable claim for relevance, participating actively in the interdisciplinary exchange of ideas.     

Inertia and Managerial Intentionality: Extending the Uppsala Model

The Uppsala Internationalization Process Model is the most cited model within the field of international business. However, even with its most recent formulation, the model is predicated on a key set of assumptions about the limiting and releasing mechanisms in a ‘change of state’ decision. The model assumes that uncertainty, risk, lack of trust, and lack of awareness of opportunities are the main constraints, and that the accumulation of experiential knowledge, trust, and market commitment are the main releasing factors that allow a firm to overcome those constraints and progress to a higher state of commitment. We argue that the preceding view may be excessively narrow, and that inertia and managerial intentionality may also play a role as critical limiting and releasing mechanisms, respectively. This development implies that the passage of time and experiential learning may not always have a positive impact on firm internationalization. The extended model proposed in this paper highlights the role of the manager, and brings a contingent element to the model, thus broadening its applicability by providing new insights on issues typically considered outside the realm of the Uppsala model, such as rapidly internationalizing firms, regionalization, mode inertia and mode skipping.     

Fuzzy-c-mean algorithm for codebook design in vector quantisation

The fuzzy-c-mean algorithm (FCM), well known in cluster analysis, is introduced to codebook design in vector quantisation. It is examined for the vector space of DCT coefficients and compared with the LBG algorithm which is normally used in vector quantisation     

L-735,334, a novel sesquiterpenoid potassium channel-agonist from Trichoderma virens

A novel oleic acid ester of the carotane sesquiterpene 14-hydroxy CAF-603 was isolated from Trichoderma virens grown in a solid brown rice-based medium, a solid millet-based medium, or a mannitol-based liquid medium. Its structure was determined on the basis of ms and nmr analysis. It retains distinct biological activity on the high conductance calcium-activated potassium channel, unlike its analogues 14-hydroxy CAF-603, CAF-603 3-oleate, or CAF-603 3-linoleate.