170,080 research outputs found
Pigments in extra-virgin olive oils produced in Tuscany (Italy) in different years
No full textPigments are responsible of the color of olive oils, an important feature defining their aspect, related to the quality of this food. However, the concentration of pigments can vary significantly depending on the climate conditions, harvesting time and olives cultivars. In this work, we quantified the main pigments in several extra-virgin olive oils produced from a blend of three cultivars (Moraiolo, Frantoio and Leccino) typical of Tuscany (Italy) harvested in three different years: 2012, 2013 and 2014. Pigments, namely beta-carotene, lutein, pheophytin A and pheophytin B, were quantified by a method based on the mathematical analysis of the near UV-visible absorption spectra of the oils. Data were analyzed by a multivariate statistical approach. The results show that the pigments’ content of extra-virgin olive oils produced in 2014 can be well distinguished with respect to previous years. This can be explained with the anomalous climate conditions, which strongly affected Italy and, in particular, Tuscany, where the olives were harvested. This study represents an interesting example of how pigments’ content can be significant in characterizing olive oils. Moreover, this is the first report of pigments’ quantification in extra-virgin olive oils produced in Tuscany
Valutazione dei difetti perimetrici glaucomatosi mediante perimetria automatica con programma soglia C/30-2 e programma Esterman- Atti Società Oftalmologica Lombarda
No full textSi valutano i difetti perimetrici glaucomatosi mediante perimetria automatica con programma soglia C/30-2 e programma Esterma
A modified fuzzy C-means algorithm for feature selection
No full textIn this paper we propose a novel method for feature selection based on a modified fuzzy C-means algorithm with supervision (MFCMS). MFCMS adopts an appropriately modified version of the objective function used by the classic fuzzy C-means. We applied MFCMS to some real-world pattern classification benchmarks. To test the effectiveness of MFCMS as feature selector, we used the well-known k-nearest neighbor as learning algorithm. In our experiments we found that the classification performance using the set of features selected by MFCMS is better than that using all the original features. Furthermore, our approach proved to be less time-consuming than other feature selection methods
Risk factors for mortality from pneumonia in children in low and middle income countries: systematic review (protocol and preliminary results).
No full textBackground
Pneumonia is the most common cause of mortality in children under five years of age.
Aims
To systematically review the evidence on the risk factors for death from pneumonia in children in low and middle income countries.
Methods
We will searched MEDLINE, EMBASE, LILACS, CINAHL, BIBLIOMAP, POPLINE, for published studies. For ongoing studies we will search the WHO Platform (ICTRP), MetaRegister of Controlled Trials (mRCT), Current Controlled Trials (CCT). We will contact a list researchers working in the field, technical bodies and academic institutions. We will include for evaluation the following types of risk factors: a) Biological; b) Related to the disease; c) Environmental; d) Socio-economical; e) Health Services factors. Two authors will assess study eligibility and methodological quality and extract and analyse data. Where appropriate, we will combined data in meta-analyses (random-effects model) and assess heterogeneity. Heterogeneity will be explored by subgroup analysis, and if appropriate, by meta-regression.
Results
We identified so far 58 studies, including 66,775 children, both in hospital and community setting. Preliminary results show that factors significantly related to mortality pertain to all five categories evaluated: a) Biological factors (age, birth-weight, malnutrition, co-morbidities such as HIV, sepsis, diarrhoea -with some heterogeneity among studies, anaemia, rickets); b) Factors related to the disease (severity of pneumonia, hypoxia, disease duration, disease extension, bacterial disease); c) Environmental factors (indoor pollution); d) Socio-economical factors (maternal education); e) Health Services factors (health-worker visit, previous treatment).
Conclusion
Final results of this work will be available for presentation at the meeting
Pigments in extra virgin olive oils produced in different mediterranean countries in 2014: Near UV-vis spectroscopy versus HPLC-DAD
No full textCarotenoids and chlorophyll derivatives play a key role in Extra Virgin Olive Oils (EVOOs). Many factors,
such as cultivar, geographic origin, maturity of olives, climate and storage conditions, influence the
pigments’ content. The quantification of pigments is usually done by chromatographic techniques.
However, recent works evidenced the potentialities of UV-visible-related methodologies. In this
research, a selection of EVOO samples produced from olives harvested at the beginning of November
2014 in Greece, Tunisia, Italy and Spain, was investigated in terms of pigments by means of two methods.
The first one is a recent approach based on the mathematical treatment of near UV-vis absorption spectra
of olive oils to quantify in a fast, cheap and non-destructive way four main pigments, namely b-carotene,
lutein, pheophytin A and pheophytin B. The second one is a more standard HPLC-DAD method. From the
comparison between the two methods, we can conclude that the new near UV-vis approach gives
reliable results, with good precision and high reproducibility. Pigments quantified by these two methods
in EVOOs produced in four countries from different cultivars are analyzed by principal component
analysis (PCA). Results indicate that pigments can be correlated to several factors such as ripeness stage,
geographic origin and cultivars
A new fuzzy relational clustering algorithm based on the fuzzy C-means algorithm
No full textIn this paper, we show how one can take advantage of the stability and effectiveness of object data clustering algorithms when the data to be clustered are available in the form Of Mutual numerical relationships between pairs of objects. More precisely, we propose a new fuzzy relational algorithm, based on the popular fuzzy C-means (FCM) algorithm, which does not require any particular restriction on the relation matrix. We describe the application of the algorithm to four real and four synthetic data sets, and show that our algorithm performs better than well-known fuzzy relational Clustering algorithms on all these sets
Valutazione dei difetti perimetrici glaucomatosi mediante perimetria automatica con programma soglia C/30-2 e programma Esterman
No full textValutazione dei difetti perimetrici glaucomatosi mediante perimetria automatica con programma soglia C/30-2 e programma Esterma
Sclerostomia con laser ad Olmio. Risultati a lungo termine [Holmium laser sclerostomy long-term results]
No full textSi studiano i risultati a lungo termine della Sclerostomia con laser ad Olmio
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