Scientific relations between Spain and central-Eastern European countries for the period 1982–1992
This paper analyzes the scientific relationships between Spain and the Eastern European countries (EEc), including the former USSR, from 1982 to 1992. The study considers the number of co-authored papers as well as the number of stays which reflect to the exchange of scientists among them. The total number of co-authored papers of Spanish scientists with their colleagues of those countries is 664 as recorded in theScience Citation Index. During the last three years, a significative increase in the number of co-signed papers has been observed. From the sample considered, the percentage of bilateral and multilateral co-authored papers is 43.8 and 56.2 respectively. In absolute figures, USSR and Poland are the countries with highest number of collaborative papers with Spain. However, in relation to their scientific output, Poland and Hungary show a higher percentage of co-authored papers than the rest of EEc. On the other hand, previous data, provided by the Spanish Secretary of State for Research and Universities (SEUI), related to the flow of scientists on sabbatical year to and from Spain,1 showed that from 1984 to 1994, a total of 213 researches come from the EEc to Spain, while the number of Spanish scientists going to those countries was extremely scarce.
International cooperation of polish researchers with partners from abroad: A scientometric study
Publications resulting from international cooperation and included in seven SCI annual files 1987–1989 and 1992–1995 were analyzed. It was observed that after the political changes of the turn of 1980s considerable increase in the number of publications was accompanied by the geographic development of co-authorship. Information coming from SCI 1992–1995, elaborated, completed and encoded were entered into an own database designed for analytical purposes. During these four years above 9600 papers were published in over 1600 prestige journals, of which almost 2200 publications resulted from multilateral cooperation. Altogether the foreign coauthors came from 102 countries, but over 80% of international papers were published in cooperation with the partners from 11 countries. The domestic participants came from over 200 research and educational organizations. It was found that the biggest share of papers within this multidisciplinary file represented physics (≈40%), chemistry (≈21%), and biomedical research (≈11%).
Robust solutions of inverse problems in electromagnetic non-destructive evaluation
Non-destructive testing (NDT) is the application of physical measurement technology based on energy interaction with the material and its nonconformities. The material's response is sensed by transducers and sensors which?in most cases?scan the component and document the results in inspection images. However, NDT measures a physically defined quantity or even an intrinsic property. The difference between non-destructive evaluation (NDE) and NDT is in the interpretation of the inspection data. NDE has to discuss the inspection results in terms of quality elements and characteristics which are relevant to describe the fitness of the material for use. In the case of macroscopic defects these are the kind of defect (cracklike, globular) and its size and orientation to the main stress directions; in the case of material property determination the parameters are mainly mechanical properties. Therefore, in NDE one has to solve inverse problems. The solution of inverse problems based on mathematical procedures such as integral equations is a strong developing discipline and most of the articles prepared for this special issue of the journal have the objective of discussing the latest state of the art in that field. However, practical NDE needs robust and quick solutions which are to be applied mainly online. Therefore, we present here inversion procedures based on multiple linear regression algorithms applied to inspection data. We describe the calibration procedure to fit the free parameters of the model functions and give examples of practical applications in industry.