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Abstract  

Bio-pharmaceutical R&D is increasingly an international affair. Research articles published in the peer-reviewed international scientific and technical journals represent quantifiable research outputs of bio-pharmaceutical firms. Large-scale systemic measurements of worldwide trends and sectoral patterns within bio-pharmaceutical science can be gauged from these articles, where coauthored research papers are assumed to reflect research cooperation and associated knowledge flows and exchanges. We focus our attention on the largest science-based multinational enterprises (MNEs), those that produce relatively large quantities of research articles. The study deals with the worldwide output of research articles that are co-produced by corporate researchers during the years 1996–2001. We employ these publications to examine structural factors characterizing research cooperation networks within industry at the level of major geographical regions (North America, Europe, Pacific-Asia), with a breakdown by within-MNE and between-MNE network linkages. The descriptive statistics on publication output and results of network analyses of co-publication linkages not only indicate regional differences, with a central role for US companies in biopharmaceutical research, but also a variety of firm-specific research cooperation networks which enabled us to develop a tentative typology of MNEs in terms of their intra- and interorganizational patterns of research cooperation linkages.

Open access

. In addition, even devoted experts might be unaware of every relevant scale across psychology, psychiatry, and health. Initial Semantic Scale Network analyses ( Rosenbusch, Wanders, & Pit, 2020 ), which examine the content of the questions (rather than

Open access

Abstract

The article highlights the worldwide dissemination of precision agriculture scientific researches published from the period of 1996–2018, data gathered in the Scopus citation database, using the science mapping method. The findings show that there is a constant rise in the number of publications in precision agriculture. The USA is not only leading in the adoption of precision agriculture technologies but also in the publication of papers, accompanied by China placed in second place. The most frequent keywords highlighted the main topics authors concentrated on more, and the national affiliation of most cited papers was the USA. The main prominence and contributions of the results present scientific research trends in precision agriculture in the last two decades, and demonstrate the main countries, authors and organizations who have contributed, and were more productive in this area.

Open access

Abstract  

The aim of this paper is to describe how a dynamic mechanical analyser can be used together with the microwave coaxial line technique. This coupling enables the simultaneous recording of changes in the mechanical properties and moisture content of materials as a function of time or temperature at a selected frequency. The sample is placed either directly under the probe or clamped in the sample holder of the dynamic mechanical analyser. Sample positioning and heating is accurately controlled by the mechanical analyser and its temperature controller. Samples can be subjected to a constant static force, a frequency or both. A micro probe, recently designed for measurements on semi-rigid and rigid surfaces [1], and connected to a network analyser was used to monitor the moisture content of the samples.

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Nowadays, the Continuously Operating Reference Station (CORS) network, combined with network RTK corrections (NRTK solution), is a widely used technique for high-accuracy positioning in real time. This “active” network realizes a reference frame and propagates it to the users. In border regions the coherence between the reference frames propagated by neighboring active networks is a critical problem. In this study the test results of post-processed and simultaneous NRTK positions at six test points located in the border region between Portugal and the Community of Andalusia, in the south west of the Iberian Peninsula, are presented. The analysis is based on two GNSS active networks present in this border region, namely RENEP (Portugal) and RAP (Community of Andalusia, Spain), a national and a local RTK network respectively, with similar characteristics. Upon comparing the post-processed position for each test point, as estimated with respect to each of the two active networks analyzed, the discrepancies found in 3D were less than 2 centimeters. The results of network-based RTK positioning were found to be successful within a 2 cm precision level in the east and north components and 4 cm for the up component. The results also confirm that the NRTK positioning accuracy is about 2 cm in horizontal and 4 cm in vertical, which can satisfy the requirement of real-time positioning users at a centimetric accuracy level, even in border regions considering extrapolated NRTK solutions.

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Conservation of species is often focused either only on those that are endangered, or on maximising the number recorded on species lists. However, species share space and time with others, thus interacting and building frameworks of relationships that can be unravelled by community-level network analysis. It is these relationships that ultimately drive ecosystem function via the transfer of energy and nutrients. However interactions are rarely considered in conservation planning. Network analysis can be used to detect key species (“hubs”) that play an important role in cohesiveness of networks. We applied this approach to plant-pollinator communities on two montane Northern Apennine grasslands, paying special attention to the modules and the identity of hubs. We performed season-wide sampling and then focused the network analyses on time units consistent with plant phenology. After testing for significance of modules, only some modules were found to be significantly segregated from others. Thus, networks were organized around a structured core of modules with a set of companion species that were not organized into compartments. Using a network approach we obtained a list of important plant and pollinator species, including three Network Hubs of utmost importance, and other hubs of particular biogeographical interest. By having a lot of links and high partner diversity, hubs should convey stability to networks. Due to their role in the networks, taking into account such key species when considering the management of sites could help to preserve the greatest number of interactions and thus support many other species.

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Abstract

This study examines the impact of collaborating patterns on the R&D performance of public research institutions (PRIs) in Korea's science and engineering fields. For the construction of R&D collaborating networks based on the co-authorship data of 127 institutions in Scopus, this paper proposes four types of collaborations by categorizing network analyses into two dimensions: structural positions (density, efficiency, and betweeness centrality) and the relational characteristics of individual nodes (eigenvector and closeness centralities). To explore the research performance by collaboration type, we employ a data envelopment analysis window analysis of a panel of 23 PRIs over a 10-year period. Comparing the R&D productivities of each group, we find that the PRIs of higher productivity adhere to a cohesive networking strategy, retaining intensive relations with their existing partners. The empirical results suggest that excessively cohesive alliances might end up in ‘lock-in’ relations, hindering the exploitation of new opportunities for innovation. These findings are implicit in relation to the Korean Government's R&D policies on collaborating strategies to produce sustained research results with the advent of the convergence research era.

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Scientometrics
Authors: Christian Gumpenberger, Juan Gorraiz, Wolfgang Glänzel, Koenrad Debackere, Stefan Hornbostel, and Sybille Hinze

background and techniques of “Mapping Science” and “Network Analyses”. After the lunch break Matthias Winterhager (Bielefeld University, Germany) showed quite plainly “What to do (and not to do) with corporate data” and pointed out the well-known issues

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2002 ). Commercial bibliometric databases and repositories of open access journals have contributed to network analyses by offering citation indexes and data on co-author relationships. Typical applications of the results of network analyses of

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COVID–19 járvány hatása a pszichiátriai megbetegedések gyakoriságára – PTSD

Effects of the COVID-19 pandemic on the incidence of psychiatric illnesses – PTSD

Scientia et Securitas
Authors: Mária Zsóka Bellavics, Zsombor Hermann, and József Haller

References 1 Armour, C., Fried, E. I., & Olff, M. (2017) PTSD symptomics: network analyses in the field of psychotraumatology. European Journal of

Open access