Networks and navigation in the knowledge economy: Studies on the structural conditions and consequences of path-dependent and relational action

In the wake of a relational turn, economic geographers have begun to scrutinize the relationships and interactions between people and organizations as a driving force behind economic processes at both global and local scales. Through a focus on contingent contextuality and path dependence, relational economic geography and network thinking have provided the necessary conceptual toolbox for untangling the structural effects and drivers of these relationships and their spatial embeddedness. However, despite the conceptual richness of the relational approach, empirical studies have often fallen short of capturing its core tenets: First, there is a prevalence to focus on places, infrastructures, and similarities as aggregate proxies for actors and their socio-economic relationships as the unit of geographical network analysis; While often convenient, this approach misses out on the capacity of networks to represent spatially embedded social contexts as enablers or constraints of economic action. Second, while path dependence is at the heart of evolutionary approaches towards economic geography, few studies actually trace how path-dependent and interrelated innovation shapes the long-term emergence of fields. Relational processes are especially salient when outcomes are opaque, decisions are interdependent, and when formal rules and roles are weak or absent. In this thesis, I ask how actors navigate such contexts and investigate the structural conditions and consequences of their navigation efforts. In my pursuit of this question, I draw on literatures from sociology, economics, and organization studies and build on novel methods of network analysis capable of empirically capturing contextuality and path dependence to investigate relational processes at three levels of economic activity: The thesis first looks towards a localized and informal trade platform to demonstrate how consumers rely on their former transactions to navigate exchange uncertainty and how such an exchange system can become liable to personal lock-in. It then moves on to show how the geographically and organizationally diversified search for innovation opportunities structures the transfer of knowledge across a globalized and partially informal corporate scouting community. Finally, the thesis shows how the linkage of distinct knowledge domains drives the long-term emergence of heterogeneous technological fields. In its endeavor to trace these processes, the thesis contributes a set of distinct relational research designs that demonstrate how advances in methods and data can be employed to empirically exploit the conceptual richness of relational economic geography

Chapter The Airborne Internet

Mineralogy & gem

The Airborne Internet

Mineralogy & gem

HEPchain: Novel Proof-of-Useful-Work blockchain consensus for High Energy Physics

Monte Carlo simulations play a crucial role in all stages of particle collider experiments. There has been a long-term trend in HEP of both increasing collision energies and the luminosity. As a result, the requirements for MC simulations have become more rigorous: Their computational complexity has increased due to higher accuracy requirements. Additionally, more simulation data is required to allow data analysts to spot Standard Model deviations in observations of real data and enable the filtering of rare events. In order to keep up with the computational complexity of simulations and analysis of real data, distributed computing approaches are commonly employed. For instance, CERN relies on the Worldwide LHC Computing Grid (WLCG) in order to be able to store, process, distribute and analyze collision data. Since not every HEP experiment has access to these resources and the addition of new Grid servers is a complex process, this publication explores a novel distributed computing approach for HEP which is based on blockchain technology. It features the description of a novel Proof-of-Useful-Work consensus algorithm which aims to both support real-world HEP experiments with the production of required MC data and to secure the underlying blockchain infrastructure at the same time. Instead of being an alternative to WLCG or BOINC projects that rely on volunteer computing, it aims to be a complementary source of additional computing power. This publication also features a brief introduction into blockchain fundamentals and comparisons to existing distributed computing approaches.Comment: This is a Draft version that might be subjected to changes in the futur

COVID-19 in Latin America: Where We Stand and What Is to Come

As infection rates decrease, much of Latin America seems to be taking a breather from the onslaught of COVID-19. However access to vaccines is unequal, both within and between individual countries, while vaccine coverage is heterogeneous. Combined with uneven infection rates and the arrival of the highly contagious Delta variant, new epidemiological and policy challenges must be addressed. With 45 million registered infections and almost one-third of all COVID-19-related deaths worldwide, Latin America has become a global hotspot in the pandemic. While Chile and Costa Rica have higher vaccination rates than Germany or the United States, half of Latin America's population has yet to receive their first jab. What may come to the rescue are the high numbers of people who have acquired some immunity from past COVID-19 infections beyond those identified in official statistics. Vaccine diplomacy has changed colours. Initially, Latin America depended on vaccine shipments from China, India, and Russia. By now, the US and the multilateral COVAX initiative have become the largest providers. Policies will need to adjust to the resulting mix of vaccines of varying efficacy and varying international recognition. To reduce external dependence, the region will need to build up its capacity to develop and mass-produce vaccines, diagnostic equipment, and mRNA technology. The vaccines developed in Cuba could become part of the vaccine portfolio the continent will need for many years to come. The pandemic has exposed the region's structural weaknesses. Public-health funding must be stepped up; ad hoc social-policy measures taken in the pandemic should be harnessed to make social safety nets more resilient and inclusive. A strong vaccination drive remains key to keeping the pandemic at bay. As immunity - whether from past infection or vaccination - will eventually wane, vaccination may need to be integrated into routine preventive healthcare. Cooperation transcending ideological left-right dichotomies in epidemiological diagnosis, research, vaccination, and healthcare provision must become a priority within the region as well as for international partners

Self-diffusion and Cooperative Diffusion in Semidilute Polymer Solutions as measured by Fluorescence Correlation Spectroscopy

We present a comprehensive investigation of polymer diffusion in the semidilute regime by fluorescence correlation spectroscopy (FCS) and dynamic light scattering (DLS). Using single-labeled polystyrene chains, FCS leads to the self-diffusion coefficient while DLS gives the cooperative diffusion coefficient for exactly the same molecular weights and concentrations. Using FCS we observe a new fast mode in the semidilute entangled concentration regime beyond the slower mode which is due to self-diffusion. Comparison of FCS data with data obtained by DLS on the same polymers shows that the second mode observed in FCS is identical to the cooperative diffusion coefficient measured with DLS. An in-depth analysis and a comparison with current theoretical models demonstrates that the new cooperative mode observed in FCS is due to the effective long-range interaction of the chains through the transient entanglement network