Publication and patent analysis of European researchers in the field of production technology and manufacturing systems

This paper develops a structured comparison among a sample of European researchers in the field of Production Technology and Manufacturing Systems, on the basis of scientific publications and patents. Researchers are evaluated and compared by a variegated set of indicators concerning (1) the output of individual researchers and (2) that of groups of researchers from the same country. While not claiming to be exhaustive, the results of this preliminary study provide a rough indication of the publishing and patenting activity of researchers in the field of interest, identifying (dis)similarities between different countries. Of particular interest is a proposal for aggregating analysis results by means of maps based on publication and patent indicators. A large amount of empirical data are presented and discusse

The success-index: an alternative approach to the h-index for evaluating an individual's research output

Among the most recent bibliometric indicators for normalizing the differences among fields of science in terms of citation behaviour, Kosmulski (J Informetr 5(3):481-485, 2011) proposed the NSP (number of successful paper) index. According to the authors, NSP deserves much attention for its great simplicity and immediate meaning— equivalent to those of the h-index—while it has the disadvantage of being prone to manipulation and not very efficient in terms of statistical significance. In the first part of the paper, we introduce the success-index, aimed at reducing the NSP-index's limitations, although requiring more computing effort. Next, we present a detailed analysis of the success-index from the point of view of its operational properties and a comparison with the h-index's ones. Particularly interesting is the examination of the success-index scale of measurement, which is much richer than the h-index's. This makes success-index much more versatile for different types of analysis—e.g., (cross-field) comparisons of the scientific output of (1) individual researchers, (2) researchers with different seniority, (3) research institutions of different size, (4) scientific journals, etc

Proposals for evaluating the regularity of a scientist'sresearch output

Evaluating the career of individual scientists according to their scientific output is a common bibliometric problem. Two aspects are classically taken into account: overall productivity and overall diffusion/impact, which can be measured by a plethora of indicators that consider publications and/or citations separately or synthesise these two quantities into a single number (e.g. h-index). A secondary aspect, which is sometimes mentioned in the rules of competitive examinations for research position/promotion, is time regularity of one researcher's scientific output. Despite the fact that it is sometimes invoked, a clear definition of regularity is still lacking. We define it as the ability of generating an active and stable research output over time, in terms of both publications/ quantity and citations/diffusion. The goal of this paper is introducing three analysis tools to perform qualitative/quantitative evaluations on the regularity of one scientist's output in a simple and organic way. These tools are respectively (1) the PY/CY diagram, (2) the publication/citation Ferrers diagram and (3) a simplified procedure for comparing the research output of several scientists according to their publication and citation temporal distributions (Borda's ranking). Description of these tools is supported by several examples

Combining Physical galaxy models with radio observations to constrain the SFRs of high-z dusty star forming galaxies

We complement our previous analysis of a sample of z~1-2 luminous and ultra-luminous infrared galaxies ((U)LIRGs), by adding deep VLA radio observations at 1.4 GHz to a large data-set from the far-UV to the sub-mm, including Spitzer and Herschel data. Given the relatively small number of (U)LIRGs in our sample with high S/N radio data, and to extend our study to a different family of galaxies, we also include 6 well sampled near IR-selected BzK galaxies at z~1.5. From our analysis based on the radiative transfer spectral synthesis code GRASIL, we find that, while the IR luminosity may be a biased tracer of the star formation rate (SFR) depending on the age of stars dominating the dust heating, the inclusion of the radio flux offers significantly tighter constraints on SFR. Our predicted SFRs are in good agreement with the estimates based on rest-frame radio luminosity and the Bell (2003) calibration. The extensive spectro-photometric coverage of our sample allows us to set important constraints on the SF history of individual objects. For essentially all galaxies we find evidence for a rather continuous SFR and a peak epoch of SF preceding that of the observation by a few Gyrs. This seems to correspond to a formation redshift of z~5-6. We finally show that our physical analysis may affect the interpretation of the SFR-M* diagram, by possibly shifting, with respect to previous works, the position of the most dust obscured objects to higher M* and lower SFRs.Comment: 26 pages, 15 figures, 3 tables, accepted for publication in MNRAS on Dec. 4th, 201

A co-ultramicronized palmitoylethanolamide/luteolin composite mitigates clinical score and disease-relevant molecular markers in a mouse model of experimental autoimmune encephalomyelitis

Background: Persistent and/or recurrent inflammatory processes are the main factor leading to multiple sclerosis (MS) lesions. The composite ultramicronized palmitoylethanolamide, an endogenous N-acylethanolamine, combined with the flavonoid luteolin, PEALut, have been found to exert neuroprotective activities in experimental models of spinal and brain injury and Alzheimer disease, as well as a clinical improvement in human stroke patients. Furthermore, PEALut enhances the expression of different myelin proteins in oligodendrocyte progenitor cells suggesting that this composite might have protective effects in MS experimental models. Methods: The mouse model of experimental autoimmune encephalomyelitis (EAE) based on active immunization with a fragment of myelin oligodendrocyte glycoprotein (MOG35-55) was used. The daily assessment of clinical score and the expression of serum amyloid A (SAA1), proinflammatory cytokines TNF-\u3b1, IL-1\u3b2, IFN-\u3b3, and NLRP3 inflammasome, as well as TLR2, Fpr2, CD137, CD3-\u3b3, and TCR-\u3b6 chain, heterodimers that form T cell surface glycoprotein (TCR), and cannabinoid receptors CB1, CB2, and MBP, were evaluated in the brainstem and cerebellum at different postimmunization days (PIDs). Results: Vehicle-MOG35-55-immunized (MOG35-55) mice developed ascending paralysis which peaked several days later and persisted until the end of the experiment. PEALut, given intraperitoneally daily starting on day 11 post-immunization, dose-dependently improved clinical score over the range 0.1-5 mg/kg. The mRNA expression of SAA1, TNF-\u3b1, IL-1\u3b2, IFN-\u3b3, and NLRP3 were significantly increased in MOG35-55 mice at 14 PID. In MOG35-55 mice treated with 5 mg /kg PEALut, the increase of SAA1, TNF- \u3b1, IL-1\u3b2, and IFN-\u3b3transcripts at 14 PID was statistically downregulated as compared to vehicle-MOG35-55 mice (p < 0.05). The expression of TLR2, Fpr2, CD137, CD3-\u3b3, TCR-\u3b6 chain, and CB2 receptors showed a significant upregulation in vehicle-MOG35-55 mice at 14 PID. Instead, CB1 and MBP transcripts have not changed in expression at any time. In MOG/PEALut-treated mice, TLR2, Fpr2, CD137, CD3-\u3b3, TCR-\u3b6 chain, and CB2 mRNAs were significantly downregulated as compared to vehicle MOG35-55 mice. Conclusions: The present results demonstrate that the intraperitoneal administration of the composite PEALut significantly reduces the development of clinical signs in the MOG35-55 model of EAE. The dose-dependent improvement of clinical score induced by PEALut was associated with a reduction in transcript expression of the acute-phase protein SAA1, TNF-\u3b1, IL-1\u3b2, IFN-\u3b3, and NLRP3 proinflammatory proteins and TLR2, Fpr2, CD137, CD3-\u3b3, TCR-\u3b6 chain, and CB2 receptors