32 research outputs found

    A quantitative multivariate methodology for unsupervised class identification in pistachio (Pistacia vera L.) plant leaves size

    Get PDF
    Aim of study: Genetic diversity of pistachio, can be evaluated by using different descriptors, as adopted in international certification systems. Mainly the descriptors are morphological traits as leaf, which represents an important organ for its sensibility to growth conditions during the expansion phase. This study adopted a rapid and quantitative non-hierarchic clustering classification (k-means), to extract size classes basing on the contemporary combination of different morphological traits (i.e., leaf stalk length, terminal leaf length, terminal leaf width and terminal leaf ratio) of a varietal collection composed by 21 pistachio cultivars.Area of study: Worldwide.Material and methods: The unsupervised non-hierarchic clustering technique was adopted to the entire samples of pistachio leaves from k=2 to k=15 for both four morphological variables (i.e., leaf stalk length, terminal leaf length, terminal leaf width and terminal leaf ratio) and three morphological variables (i.e., terminal leaf length, terminal leaf width and terminal leaf ratio).Main results: A classification model only on the three morphological variables (for results of statistical analysis in which the groups resulted to be more separated and different for all the variables), with k= 5 (five groups), was constructed using a non-linear artificial neural network approach. The percentages of bad prediction in both training and testing resulted equal to 0%. The “terminal leaf length” returned the higher impact (44.89%).Research highlights: The contemporary combination of different morphological leaf traits, allowed to create an automatic classification of size classes of great importance for cultivar identification and comparison

    Survival of Infants Born to HIV-Positive Mothers, by Feeding Modality, in Rakai, Uganda

    Get PDF
    Data comparing survival of formula-fed to breast-fed infants in programmatic settings are limited. We compared mortality and HIV-free of breast and formula-fed infants born to HIV-positive mothers in a program in rural, Rakai District Uganda.One hundred eighty two infants born to HIV-positive mothers were followed at one, six and twelve months postpartum. Mothers were given infant-feeding counseling and allowed to make informed choices as to whether to formula-feed or breast-feed. Eligible mothers and infants received antiretroviral therapy (ART) if indicated. Mothers and their newborns received prophylaxis for prevention of mother-to-child HIV transmission (pMTCT) if they were not receiving ART. Infant HIV infection was detected by PCR (Roche Amplicor 1.5) during the follow-up visits. Kaplan Meier time-to-event methods were used to compare mortality and HIV-free survival. The adjusted hazard ratio (Adjusted HR) of infant HIV-free survival was estimated by Cox regression. Seventy-five infants (41%) were formula-fed while 107 (59%) were breast-fed. Exclusive breast-feeding was practiced by only 25% of breast-feeding women at one month postpartum. The cumulative 12-month probability of infant mortality was 18% (95% CI = 11%–29%) among the formula-fed compared to 3% (95% CI = 1%–9%) among the breast-fed infants (unadjusted hazard ratio (HR)  = 6.1(95% CI = 1.7–21.4, P-value<0.01). There were no statistically significant differentials in HIV-free survival by feeding choice (86% in the formula-fed compared to 96% in breast-fed group (Adjusted RH = 2.8[95%CI = 0.67–11.7, P-value = 0.16]Formula-feeding was associated with a higher risk of infant mortality than breastfeeding in this rural population. Our findings suggest that formula-feeding should be discouraged in similar African settings

    "Prevenzioni delle lesioni corneali da elettrodo per elettroretinografia con soluzione di idrossipropilcellulosa 0,4%".

    No full text
    In this study, a statisthical analysis of 100 patients undergone to electroretinogram shows the opportuneness to use an artificial tears solution to prevent the electrode damage of the cornea

    A quantitative multivariate methodology for unsupervised class identification in pistachio (Pistacia vera L.) plant leaves size

    No full text
    Aim of study: Genetic diversity of pistachio, can be evaluated by using different descriptors, as adopted in international certification systems. Mainly the descriptors are morphological traits as leaf, which represents an important organ for its sensibility to growth conditions during the expansion phase. This study adopted a rapid and quantitative non-hierarchic clustering classification (k-means), to extract size classes basing on the contemporary combination of different morphological traits (i.e., leaf stalk length, terminal leaf length, terminal leaf width and terminal leaf ratio) of a varietal collection composed by 21 pistachio cultivars.Area of study: Worldwide.Material and methods: The unsupervised non-hierarchic clustering technique was adopted to the entire samples of pistachio leaves from k=2 to k=15 for both four morphological variables (i.e., leaf stalk length, terminal leaf length, terminal leaf width and terminal leaf ratio) and three morphological variables (i.e., terminal leaf length, terminal leaf width and terminal leaf ratio).Main results: A classification model only on the three morphological variables (for results of statistical analysis in which the groups resulted to be more separated and different for all the variables), with k= 5 (five groups), was constructed using a non-linear artificial neural network approach. The percentages of bad prediction in both training and testing resulted equal to 0%. The “terminal leaf length” returned the higher impact (44.89%).Research highlights: The contemporary combination of different morphological leaf traits, allowed to create an automatic classification of size classes of great importance for cultivar identification and comparison

    Studio preliminare degli effetti dell'alfentanil sul tono endoculare.

    No full text
    corecore