Fetal polyuria and decrease of electrolytes in amniotic fluid as principal markers of neonatal Bartter''s syndrome]

The above mentioned after a careful investigation of the modern pathogenic aspects of Bartter's syndrome, evaluated the markers that are useful for the prenatal diagnosis of Bartter's syndrome, they pointed out, as in both cases the presence of polyhydramnios not associated with ecographically detectable fetal malformations, elevated chloride in the amniotic fluid, accompanied in one case by increased levels of aldosterone, in the other case by the increase of K, as being reliable markers for the prenatal diagnosis of these conditions.     

Polyphenolic pattern and in vitro cardioprotective properties of typical red wines from vineyards cultivated in Scafati (Salerno,Italy)

Wines are the subject of increasing numbers of investigations owing to the pharmaceutical usefulness of grape phytochemicals. The aim of the present work was to hypothesize the use of lyophilised red wines for the formulation of food supplements potentially useful against both physiological and induced cardiac oxidative stress. Cardiac derived H9C2 myocytes were incubated with increasing doses (0.01–1 μg) of lyophilised Aglianico wine (lioAW). Experiments showed an appreciable direct radical scavenging activity at a maximum lioAW dose of 0.03 μg that made the caspase-3 activity decrease by about 41%. Cardiac cells were exposed to 1 μM doxorubicin and its combination with different doses of lioAW. Maximum lioAW aliquot of 0.03 μg seemed to effectively contrast the induced oxidant injury decreasing the reactive oxygen species (ROSs) levels by about 38%and depressing the caspase-3 activity by about 63%. In both assays, pro-oxidant effects at higher lioAW concentrations were detected.     

Brazilian Architect Offers Free Services to the Favelados

What's so special about offering my services for free to the favelados? — says Brazilian architect Ruy Obtake, sitting at a meeting of the residents association of Heliópolis, the biggest informal settlement in Sao Paulo.     

A queuing network model for the management of berth crane operations

This paper focuses on the optimal management of container discharge/loading at any given berthing point, within a real maritime terminal. Productivity maximization of expensive resources, as rail-mounted berth cranes, should be matched with the vessel requirement of minimizing waiting times with an adequate rate of service completion. To this practical problem, a queuing network model is proposed. Due to its complexity, discrete-event simulation appears as the most appropriate approach to model solution. To get a systematic representation of real constraints and policies of resource allocation and activity scheduling, an event graph (EG)-based methodology has been exploited in simulator design. Alternative policies issued by the operation manager can be inserted in a suitable panel-like view of the queuing network model and then compared by means of simulation, to evaluate the average measures for all berth cranes, such as throughput and completion time. Numerical experiments for simulator validation against real data are encouraging. Some decisions on both straddle carrier assignment to berth cranes and hold assignment and sequencing upon the same crane could be improved by the proposed manager-friendly simulation tool.     

Hybrid Generative-Discriminative Visual Categorization

Learning models for detecting and classifying object categories is a challenging problem in machine vision. While discriminative approaches to learning and classification have, in principle, superior performance, generative approaches provide many useful features, one of which is the ability to naturally establish explicit correspondence between model components and scene features—this, in turn, allows for the handling of missing data and unsupervised learning in clutter. We explore a hybrid generative/discriminative approach, using ‘Fisher Kernels’ (Jaakola, T., et al. in Advances in neural information processing systems, Vol. 11, pp. 487–493, 1999), which retains most of the desirable properties of generative methods, while increasing the classification performance through a discriminative setting. Our experiments, conducted on a number of popular benchmarks, show strong performance improvements over the corresponding generative approach. In addition, we demonstrate how this hybrid learning paradigm can be extended to address several outstanding challenges within computer vision including how to combine multiple object models and learning with unlabeled data.     

What is the relation between slow feature analysis and independent component analysis?

We present an analytical comparison between linear slow feature analysis and second-order independent component analysis, and show that in the case of one time delay, the two approaches are equivalent. We also consider the case of several time delays and discuss two possible extensions of slow feature analysis.     

On the analysis and interpretation of inhomogeneous quadratic forms as receptive fields

In this letter, we introduce some mathematical and numerical tools to analyze and interpret inhomogeneous quadratic forms. The resulting characterization is in some aspects similar to that given by experimental studies of cortical cells, making it particularly suitable for application to second-order approximations and theoretical models of physiological receptive fields. We first discuss two ways of analyzing a quadratic form by visualizing the coefficients of its quadratic and linear term directly and by considering the eigenvectors of its quadratic term. We then present an algorithm to compute the optimal excitatory and inhibitory stimuli--those that maximize and minimize the considered quadratic form, respectively, given a fixed energy constraint. The analysis of the optimal stimuli is completed by considering their invariances, which are the transformations to which the quadratic form is most insensitive, and by introducing a test to determine which of these are statistically significant. Next we propose a way to measure the relative contribution of the quadratic and linear term to the total output of the quadratic form. Furthermore, we derive simpler versions of the above techniques in the special case of a quadratic form without linear term. In the final part of the letter, we show that for each quadratic form, it is possible to build an equivalent two-layer neural network, which is compatible with (but more general than) related networks used in some recent articles and with the energy model of complex cells. We show that the neural network is unique only up to an arbitrary orthogonal transformation of the excitatory and inhibitory subunits in the first layer.     

Pure lycopene from tomato preserves extra virgin olive oil from natural oxidative events during storage

In this study, changes in an extra virgin olive oil treated with lycopene during storage were analyzed. Pure lycopene (0.5 and 1.0 mg) obtained from tomato was added to two separate bottles, each containing 100 mL of extra virgin olive oil, while another bottle containing the same oil was stored without any treatment. Samples enriched with pure lycopene showed PV remarkably lower than the sample without lycopene, and the total phenol contents were higher in treated oil samples than in the reference sample. In addition, a good correlation (r ²=0.969) between total phenol content and antioxidant power calculated as Trolox Equivalent Antioxidant Capacity (TEAC) was observed. The concentration of added lycopene decreased very slowly; after about 8 mon its residual value was over 60% with respect to the initial concentration.