130,522 research outputs found
Considerazioni sulla rappresentazione dei putealia e dei sistemi di approvvigionamento idrico nell'arte paleocristiana
"In fornacem ignis ardentem". Osservazioni sulla rappresentazione della fornace nei sarcofagi paleocristiani con la scena del vivicomburium
Strumenti per il raggiungimento delle coperture vaccinali, verifica della qualità delle prestazioni e valutazione dei programmi vaccinali
MeSH term explosion and author rank improve expert recommendations
Information overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
"Più di ogni altro versato in simili materie". Il ruolo di Giovanni Battista de Rossi per lo studio delle catacombe della Toscana
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Tackling the challenges of the oral administration of a fermented flour extract with liposomes: Effect on intestinal HT-29 cells
LisosanG is a fermented flour that contains polyphenols, polyunsaturated fatty acids, vitamins, and alpha-lipoic acid with antioxidant/anti-inflammatory properties. These compounds are often characterized by instability, low solubility/bioavailability, and poor absorption that restrict their application in therapy. These problems can be solved by using delivery systems among which liposomes have emerged as prominent candidates. Liposomes can load compounds with varied physico-chemical properties, providing protection from degradation, increased solubility, modulation of release, and facilitated diffusion across biomembranes. Lisosan G liposomes tailored for oral administration were prepared. Eudragit® enteric polymer was added to protect the liposomes from acidic pH. The Eudragit-liposomes were around 100 nm and unilamellar. They were resistant to acidic conditions and did not alter cell viability, nor intracellular ROS levels. These findings confirm that liposomes are an efficient system for the loading of multicomponent-based extracts and that, when properly formulated, can offer protection from physiological degradation, and be safely applied to cells
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
Both spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
Wavelet shrinkage using adaptive structured sparsity constraints
Structured sparsity approaches have recently received much attention in the statistics, machine learning, and signal processing communities. A common strategy is to exploit or assume prior information about structural dependencies inherent in the data; the solution is encouraged to behave as such by the inclusion of an appropriate regularisation term which enforces structured sparsity constraints over sub-groups of data. An important variant of this idea considers the tree-like dependency structures often apparent in wavelet decompositions. However, both the constituent groups and their associated weights in the regularisation term are typically defined a priori. We here introduce an adaptive wavelet denoising framework whereby a sparsity-inducing regulariser is modified based on information extracted from the signal itself. In particular, we use the same wavelet decomposition to detect the location of salient features in the signal, such as jumps or sharp bumps. Given these locations, the weights in the regulariser associated to the groups of coefficients that cover these time locations are modified in order to favour retention of those coefficients. Denoising experiments show that, not only does the adaptive method preserve the salient features better than the non-adaptive constraints, but it also delivers significantly better shrinkage over the signal as a whole
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