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Near Infrared Spectroscopy (NIRS), as one of analysis technologies, has shown promisingly industrial applications for significant properties for recent decades such as fast response, preciseness, non-intrusion etc. Here, the authors employed NIRS coupled with a series of physical and chemical tests to assess the ageing condition of oil-paper insulation, which is responsible for the main insulation type of high-voltage power transformer. Among these procedures, the data analytic algorithms are of utmost importance to determine the evaluation precision. After plenty of trial-and-error, Savitzky-Golay (S-G) convolution was finally utilised to de-noise samples and improve the spectral data quality. The competitive adaptive reweighted sampling (CARS) was used to select the optimal wavelength combination of NIRS, which is found able to fully extract the effectively spectral information and reduce dimensions of spectral data. Based on the above-mentioned techniques, the quantitative analysis model of NIRS was established by partial least squares (PLS), which could synthetically process the spectral data and the degree of polymerisation (DP) of paper samples. The results indicated that compared with the traditional detection methods, the NIRS analysis is a powerful and informative tool to characterise the condition of oil-paper insulation without intrusion or damage to transformers.

Near Infrared Spectroscopy (NIRS), as one of analysis technologies, has shown promisingly industrial applications for significant properties for recent decades such as fast response, preciseness, non-intrusion etc. Here, the authors employed NIRS coupled with a series of physical and chemical tests to assess the ageing condition of oil-paper insulation, which is responsible for the main insulation type of high-voltage power transformer. Among these procedures, the data analytic algorithms are of utmost importance to determine the evaluation precision. After plenty of trial-and-error, Savitzky-Golay (S-G) convolution was finally utilised to de-noise samples and improve the spectral data quality. The competitive adaptive reweighted sampling (CARS) was used to select the optimal wavelength combination of NIRS, which is found able to fully extract the effectively spectral information and reduce dimensions of spectral data. Based on the above-mentioned techniques, the quantitative analysis model of NIRS was established by partial least squares (PLS), which could synthetically process the spectral data and the degree of polymerisation (DP) of paper samples. The results indicated that compared with the traditional detection methods, the NIRS analysis is a powerful and informative tool to characterise the condition of oil-paper insulation without intrusion or damage to transformers. [ABSTRACT FROM AUTHOR]

By using the descriptive content analysis, this research study aimed to evaluate the studies on mathematics education presented within the scope of International Classroom Teaching Education Symposium (USOS) and published in proceeding book between 2014-2018. Findings of the study indicated that the number of studies conducted about mathematics teaching has increased in last five years. In terms of publishing language, the studies were in Turkish and conducted by Turkish researchers although USOS is an international scientific event. In terms of research field, the number of the studies conducted in the field of geometry and examining mathematics and geometry together is quite few. In terms of study group/sample, the research studies were conducted with elementary students, pre-service elementary teachers and elementary teachers. In terms of research model/pattern, survey and case studies were preferred by a majority. Besides, the information on research model/pattern was not stated in a majority of research studies. As a data collection tool; test, interview form, scale, open-ended question and questionnaire were mostly used. In some studies, the information about data collection tool was not given. As data analysis technique, content analysis and predictive statistical techniques were commonly used. In a majority of the studies, the information about data analysis technique was not given. [ABSTRACT FROM AUTHOR]

Background and Objective: Co-authorship on writing articles is one of the indicators of reliability in scientific articles. Due to the lack of information regarding to the rate of participation of the authors of articles in the "Iranian Journal of Pathology" this research with the aim of the survey of collaborative coefficients of article authors in this Journal from 2006 to 2012 was performed. Materials and Methods: A cross sectional research was performed. The study population consisted of all articles published in the years studied. Totally 288 printed articles in terms of number and sexes of authors were recognized and collaborative coefficient between the authors was calculated. The data were collected by referring to the original articles and Excel software was used for data entry. Data analysis with using descriptive statistics and collaborative coefficient formula was worked out. Results: Altogether 288 articles had 1078 authors. Average number of authors was 3.75 ± 1.65 and the maximum number of articles was written by three authors. Collaborative coefficient in 2008 was seen as higher ratio of collaboration between article authors. Average collaborative coefficient of authors in research years was 0.69 which demonstrated willingness to cooperate between authors of this journal. Conclusion: It seems that the collaboration between article authors of pathology is high. However considering that participation lead to increase the quality of research activities, encourage researchers to collaborate in scientific research can enhance the quality of articles. [ABSTRACT FROM AUTHOR]

Abstract: The use of radiocarbon in forensics is by now widespread, thanks to the so-called bomb peak, which makes it possible to perform high-precision dating. Since 1955, 14C concentration in the atmosphere had strongly increased due to nuclear explosions, reaching its maximum value in 1963–1965. After the Nuclear Test Ban Treaty, 14C started to decrease as a consequence of the exchanges between atmosphere and the other natural carbon reservoirs. Nowadays, it is still slightly above the pre-bomb value. The work presented in this paper is based on the idea of exploiting the bomb peak to “precisely” date works of contemporary art, with the aim at identifying possible fakes. We analysed two kinds of materials from the 20th century: newspapers and painting canvases. Newspaper samples were taken because they might in principle be considered to represent dated samples (considering the date on the issues). Our data (28 samples) show a trend similar to atmospheric data in the literature, although with some differences; the paper peak is flatter and shifted towards more recent years (about five years) with respect to the atmospheric data. This can be explained by taking paper manufacturing processes into account. As to the canvas samples, the measured 14C concentrations were generally reasonably consistent with the expected concentrations (based on the year on the paintings). However, this does not indicate that the interpretation of the results is simpler and more straightforward. Obviously, we only measure the 14C concentration of the fibre used for the canvas, which does not necessarily measure the date the painting was manufactured. In this paper, sample preparation and experimental results will be discussed, in order to show the potential as well as the limitations of radiocarbon to date contemporary art. [Copyright &y& Elsevier]

Abstract: The process of assessing individual authors should rely upon a proper aggregation of reliable and valid papers’ quality metrics. Citations are merely one possible way to measure appreciation of publications. In this study we propose some new, SJR- and SNIP-based indicators, which not only take into account the broadly conceived popularity of a paper (manifested by the number of citations), but also other factors like its potential, or the quality of papers that cite a given publication. We explore the relation and correlation between different metrics and study how they affect the values of a real-valued generalized h-index calculated for 11 prominent scientometricians. We note that the h-index is a very unstable impact function, highly sensitive for applying input elements’ scaling. Our analysis is not only of theoretical significance: data scaling is often performed to normalize citations across disciplines. Uncontrolled application of this operation may lead to unfair and biased (toward some groups) decisions. This puts the validity of authors assessment and ranking using the h-index into question. Obviously, a good impact function to be used in practice should not be as much sensitive to changing input data as the analyzed one. [Copyright &y& Elsevier]

Abstract: In the present work we introduce a modification of the h-index for multi-authored papers with contribution based author name ranking. The modified h-index is denoted by h mc-index. It employs the framework of the h m-index, which in turn is a straightforward modification of the Hirsch index, proposed by Schreiber. To retain the merit of requiring no additional rearrangement of papers in the h m-index and in order to overcome its shortage of benefiting secondary authors at the expense of primary authors, h mc-index uses combined credit allocation (CCA) to replace fractionalized counting in the h m-index. The h m-index is a special form of h mc-index and fits for papers with equally important authors or alphabetically ordered authorship. There is a possibility of an author of lower contribution to the whole scientific community obtaining a higher h mc-index. Rational h mc-index, denoted by h mcr-index, can avoid it. A fictitious example as a model case and two empirical cases are analyzed. The correlations of the h mcr-index with the h-index and its several variants considering multiple co-authorship are inspected with 30 researchers’ citation data. The results show that the h mcr-index is more reasonable for authors with different contributions. A researcher playing more important roles in significant work will obtain higher h mcr-index. [Copyright &y& Elsevier]

This manuscript focuses on two areas: the review of the history and growth of the QC/sensory evaluation field, and the discussion of the new developments and the future opportunities of this field. This discussion applies to programs worldwide, for companies with established and sound programs, and for companies with either no program or one needing improvement. From this author''s point of view, the areas or growth and opportunities include: (1) awareness of the importance of and support for QC/sensory programs within an organization, (2) increased involvement of sensory scientists in in-plant QC/sensory programs, (3) establishment of new or improved QC/sensory training programs, (4) establishment of improved sensory specifications (in techniques and the integration of consumer/management input), (5) Quality Control/sensory evaluations focused on ingredients and in-process products, (6) understanding and use of the diverse applications of product variability studies, (7) use of new or improved sensory methods, (8) collaboration between R&D and QC functions to produce high and consistent quality, (9) continued use of instrumental measures: their establishment and validation, (10) assuring minimal requirements for QC/sensory programs, (11) global Quality Control, (12) development of QC/sensory programs in the personal care, pharmaceutical, household and paper industries, (13) use of multivariate QC/sensory data analyses and control charts, (14) Internet applications in the QC/sensory field, (15) the ultimate goal: a more effective approach to deliver consistent quality products [Copyright &y& Elsevier]