Perfis de interesse de usuário de serviços de disseminação seletiva da informação: técnicas de elaboração e refinamento.

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Preliminary Assessment of Parmigiano Reggiano Authenticity by Handheld Raman Spectroscopy

Raman spectroscopy, and handheld spectrometers in particular, are gaining increasing attention in food quality control as a fast, portable, non-destructive technique. Furthermore, this technology also allows for measuring the intact sample through the packaging and, with respect to near infrared spectroscopy, it is not affected by the water content of the samples. In this work, we evaluate the potential of the methodology to model, by multivariate data analysis, the authenticity of Parmigiano Reggiano cheese, which is one of the most well-known and appreciated hard cheeses worldwide, with protected denomination of origin (PDO). On the other hand, it is also highly subject to counterfeiting. In particular, it is critical to assess the authenticity of grated cheese, to which, under strictly specified conditions, the PDO is extended. To this aim, it would be highly valuable to develop an authenticity model based on a fast, non-destructive technique. In this work, we present preliminary results obtained by a handheld Raman spectrometer and class-modeling (Soft Independent Modeling of Class Analogy, SIMCA), which are extremely promising, showing sensitivity and specificity of 100% for the test set. Moreover, another salient issue, namely the percentage of rind in grated cheese, was addressed by developing a multivariate calibration model based on Raman spectra. It was possible to obtain a prediction error around 5%, with 18% being the maximum content allowed by the production protocol

The impact of transfer learning on 3D deep learning convolutional neural network segmentation of the hippocampus in mild cognitive impairment and Alzheimer disease subjects

Research on segmentation of the hippocampus in magnetic resonance images through deep learning convolutional neural networks (CNNs) shows promising results, suggesting that these methods can identify small structural abnormalities of the hippocampus, which are among the earliest and most frequent brain changes associated with Alzheimer disease (AD). However, CNNs typically achieve the highest accuracy on datasets acquired from the same domain as the training dataset. Transfer learning allows domain adaptation through further training on a limited dataset. In this study, we applied transfer learning on a network called spatial warping network segmentation (SWANS), developed and trained in a previous study. We used MR images of patients with clinical diagnoses of mild cognitive impairment (MCI) and AD, segmented by two different raters. By using transfer learning techniques, we developed four new models, using different training methods. Testing was performed using 26% of the original dataset, which was excluded from training as a hold-out test set. In addition, 10% of the overall training dataset was used as a hold-out validation set. Results showed that all the new models achieved better hippocampal segmentation quality than the baseline SWANS model (ps <.001), with high similarity to the manual segmentations (mean dice [best model] = 0.878 ± 0.003). The best model was chosen based on visual assessment and volume percentage error (VPE). The increased precision in estimating hippocampal volumes allows the detection of small hippocampal abnormalities already present in the MCI phase (SD = [3.9 ± 0.6]%), which may be crucial for early diagnosis

Consistency conditions and trace anomalies in six dimensions

Conformally invariant quantum field theories develop trace anomalies when defined on curved backgrounds. We study again the problem of identifying all possible trace anomalies in d=6 by studying the consistency conditions to derive their 10 independent solutions. It is known that only 4 of these solutions represent true anomalies, classified as one type A anomaly, given by the topological Euler density, and three type B anomalies, made up by three independent Weyl invariants. However, we also present the explicit expressions of the remaining 6 trivial anomalies, namely those that can be obtained by the Weyl variation of local functionals. The knowledge of the latter is in general necessary to disentangle the universal coefficients of the type A and B anomalies from calculations performed on concrete models.Comment: 16 pages, LaTe

Brain Activation Patterns Characterizing Different Phases of Motor Action: Execution, Choice and Ideation.

Motor behaviour is controlled by a large set of interacting neural structures, subserving the different components involved in hierarchical motor processes. Few studies have investigated the neural substrate of higher-order motor ideation, i.e. the mental operation of conceiving a movement. The aim of this functional magnetic resonance imaging study was to segregate the neural structures involved in motor ideation from those involved in movement choice and execution. An index finger movement paradigm was adopted, including three different conditions: performing a pre-specified movement, choosing and executing a movement and ideating a movement of choice. The tasks involved either the right or left hand, in separate runs. Neuroimaging results were obtained by comparing the different experimental conditions and computing conjunction maps of the right and left hands for each contrast. Pre-specified movement execution was supported by bilateral fronto-parietal motor regions, the cerebellum and putamen. Choosing and executing finger movement involved mainly left fronto-temporal areas and the anterior cingulate. Motor ideation activated almost exclusively left hemisphere regions, including the inferior, middle and superior frontal regions, middle temporal and middle occipital gyri. These findings show that motor ideation is controlled by a cortical network mainly involved in abstract thinking, cognitive and motor control, semantic and visual imagery processes

Genetic improvement of trees for wood production, with particular refeference to wood traits

The use of selected propagation material from tree improvement programs is expected to lead to a more homogenous product, generally appreciated by industry. So far, breeding strategy have been mainly targeted to maximize acclimation/adaptation to specific environment conditions, tree growth and disease resistance, but it is not obvious that such strategy might lead to improvement of wood characteristics at the same time. Therefore, it seems important to introduce wood traits improvement as specific target of the selection process in tree breeding programs, and/or to assess heritability of wood technological properties of trees previously selected based on different criteria. Investigations reported so far have revealed that several wood traits are under a medium to high genetic control. The main goal of this work is to discuss the suitability of wood traits improvement as main target of specific breeding programs, with particular attention to wood technological characteristics to be considered in the tree selection process. Finally, we focused on noble hardwoods, that have been the target species for many improvement programs developed in Italy, and particularly on wild cherry, where studies on the genetic control of wood traits are rare

Informação para o desenvolvimento: maximização dos recursos documentários nacionais através de sistemas de comutação bibliográfica.

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L\u2019impiego di Lactobacillus acidophilus in diete per suinetti

La ricerca, condotta su suinetti a partire da 5,9 kg, ha evidenziato gli effetti favorevoli del Lactobacillus acidophilus sulla microflora intestinale rispetto ai soggetti di controllo, ma i migliori risultati anche sulle performance di accrescimento si sono ottenuti con gli antibiotici (Carbadox + Zincobacitracina)