Search results for "azioni"
showing 10 items of 4786 documents
On the structural connectivity of large-scale models of brain networks at cellular level
2021
AbstractThe brain’s structural connectivity plays a fundamental role in determining how neuron networks generate, process, and transfer information within and between brain regions. The underlying mechanisms are extremely difficult to study experimentally and, in many cases, large-scale model networks are of great help. However, the implementation of these models relies on experimental findings that are often sparse and limited. Their predicting power ultimately depends on how closely a model’s connectivity represents the real system. Here we argue that the data-driven probabilistic rules, widely used to build neuronal network models, may not be appropriate to represent the dynamics of the …
Recurrent Deep Neural Networks for Nucleosome Classification
2020
Nucleosomes are the fundamental repeating unit of chromatin. A nucleosome is an 8 histone proteins complex, in which approximately 147–150 pairs of DNA bases bind. Several biological studies have clearly stated that the regulation of cell type-specific gene activities are influenced by nucleosome positioning. Bioinformatic studies have improved those results showing proof of sequence specificity in nucleosomes’ DNA fragment. In this work, we present a recurrent neural network that uses nucleosome sequence features representation for their classification. In particular, we implement an architecture which stacks convolutional and long short-term memory layers, with the main purpose to avoid t…
Deep learning models for bacteria taxonomic classification of metagenomic data.
2018
Background An open challenge in translational bioinformatics is the analysis of sequenced metagenomes from various environmental samples. Of course, several studies demonstrated the 16S ribosomal RNA could be considered as a barcode for bacteria classification at the genus level, but till now it is hard to identify the correct composition of metagenomic data from RNA-seq short-read data. 16S short-read data are generated using two next generation sequencing technologies, i.e. whole genome shotgun (WGS) and amplicon (AMP); typically, the former is filtered to obtain short-reads belonging to a 16S shotgun (SG), whereas the latter take into account only some specific 16S hypervariable regions.…
Development of a method for the direct fermentation of semolina by selected sourdough lactic acid bacteria
2016
Three obligately heterofermentative lactic acid bacteria (LAB) strains (Lactobacillus sanfranciscensis PON100336, Leuconostoc citreum PON10079 and Weissella cibaria PON10030) were used in this study as a multi-species starter culture for sourdough production. The starter inoculum was prepared and propagated in sterile semolina extract (SSE) broth. Acidification kinetics, microbiological counts detected on specific media for sourdough LAB, polymorphic profile comparison and species-specific PCRs evidenced a stability of the liquid inoculum over time determining its suitability for direct addition to semolina. In order to validate this innovative method for the production of durum wheat (Trit…
Pasta experience: Eating with the five senses - a pilot study
2018
Dried pasta is the Italian food “par excellence”. Traditional foods have characteristics that can stimulate or evoke in the consumer sensorial stimuli and experiences, especially when these foods are consumed in a typical-traditional restaurant. Traditional restaurants can use sensory marketing as a promotional advantage, creating a unique and original atmosphere that can represent their main way of differentiation. The aims of this paper are to know consumer liking with regard to two high quality types of Sicilian pasta, common dried pasta, and whole-wheat pasta, consumed in three different venues of a typical-traditional Italian franchised restaurant, and to measure the influence of envir…
Assessment of genetically modified maize NK603 x MON810 for renewal of authorisation under Regulation (EC) No 1829/2003 (application EFSA‐GMO‐RX‐007)
2018
Efsa Panel On Genetically Modified Organisms (gmo)Scientific opinionRequestor:European Commission (DG SANTE)Question number:EFSA-Q-2017-00028; Following the submission of application EFSA-GMO-RX-007 under Regulation (EC) No 1829/2003 from Monsanto, the Panel on Genetically Modified Organisms of the European Food Safety Authority (GMO Panel) was asked to deliver a scientific risk assessment on the data submitted in the context of the renewal of authorisation application of the herbicide-tolerant and insect-resistant genetically modified maize NK603 x MON810. The data received in the context of this renewal application contained post-market environmental monitoring reports, a systematic searc…
Use of Aloe vera gel-based edible coating with natural anti-browning and anti-oxidant additives to improve post-harvest quality of fresh-cut 'Fuji' a…
2020
Recently, there is increasing use of edible and biodegradable films and packaging that are both environmentally friendly and functional for storage and market distribution. Fresh-cut &lsquo
Who Intends to Enroll in Entrepreneurship Education? Entrepreneurial Self-Identity as a Precursor
2018
Entrepreneurial self-identity is attracting increasing attention as a potentially relevant variable in explaining the entrepreneurial process. So far, most research treats entrepreneurial self-identity as a consequence of, or, at the most, as being developed through the start-up process. In this article, in contrast, we analyze its role as a previous element that helps determine the entrepreneurial intention of individuals, the perceived usefulness of entrepreneurship education, and, indirectly, their interest in participating in entrepreneurship education courses. Our hypotheses are tested on a sample of Italian university students and graduates ( N = 88) with no previous participation in…
Attention-based Model for Evaluating the Complexity of Sentences in English Language
2020
The automation of text complexity evaluation (ATCE) is an emerging problem which has been tackled by means of different methodologies. We present an effective deep learning- based solution which leverages both Recurrent Neural and the Attention mechanism. The developed system is capable of classifying sentences written in the English language by analysing their syntactical and lexical complexity. An accurate test phase has been carried out, and the system has been compared with a baseline tool based on the Support Vector Machine. This paper represents an extension of a previous deep learning model, which allows showing the suitability of Neural Networks to evaluate sentence complexity in tw…
Reverse-safe data structures for text indexing
2021
We introduce the notion of reverse-safe data structures. These are data structures that prevent the reconstruction of the data they encode (i.e., they cannot be easily reversed). A data structure D is called z-reverse-safe when there exist at least z datasets with the same set of answers as the ones stored by D. The main challenge is to ensure that D stores as many answers to useful queries as possible, is constructed efficiently, and has size close to the size of the original dataset it encodes. Given a text of length n and an integer z, we propose an algorithm which constructs a z-reverse-safe data structure that has size O(n) and answers pattern matching queries of length at most d optim…