Sperimentazione e valutazione di tecniche e strumenti di virtualizzazione per soluzioni Cloud IaaS in scenari applicativi reali

Questa tesi presenta le attività svolte durante lo stage tenuto presso la Dedalus S.p.a. riguardanti lo studio delle tecnologie di Cloud Computing esistenti,con particolare enfasi sulle soluzioni IaaS e sull'analisi di software Open Source presenti sul mercato. La Tesi presenta la realizzazione di un'infrastruttura Cloud privata per l'analisi di esperimenti e casi di studio di alcuni prodotti aziendali e la valutazione dei benefici raggiunti

Liver injury, SARS-COV-2 infection and COVID-19: What physicians should really know?

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is responsible for coronavirus disease 2019 (COVID-19), which in males, especially in advanced age, can sometimes evolve into acute respiratory distress syndrome. In addition, mild to moderate alterations in liver function tests (LFTs) have been reported in the worst affected patients. Our review aims to analyse data on the incidence and prognostic value of LFT alterations, the underlying mechanisms and the management of pre-existing liver disease in COVID-19 affected patients

Flexible Regularized Estimation in High-Dimensional Mixed Membership Models

Mixed membership models are an extension of finite mixture models, where each observation can partially belong to more than one mixture component. A probabilistic framework for mixed membership models of high-dimensional continuous data is proposed with a focus on scalability and interpretability. The novel probabilistic representation of mixed membership is based on convex combinations of dependent multivariate Gaussian random vectors. In this setting, scalability is ensured through approximations of a tensor covariance structure through multivariate eigen-approximations with adaptive regularization imposed through shrinkage priors. Conditional weak posterior consistency is established on an unconstrained model, allowing for a simple posterior sampling scheme while keeping many of the desired theoretical properties of our model. The model is motivated by two biomedical case studies: a case study on functional brain imaging of children with autism spectrum disorder (ASD) and a case study on gene expression data from breast cancer tissue. These applications highlight how the typical assumption made in cluster analysis, that each observation comes from one homogeneous subgroup, may often be restrictive in several applications, leading to unnatural interpretations of data features.Comment: arXiv admin note: text overlap with arXiv:2206.1208

Covid19/IT the digital side of Covid19: A picture from Italy with clustering and taxonomy

The Covid19 pandemic has significantly impacted on our lives, triggering a strong reaction resulting in vaccines, more effective diagnoses and therapies, policies to contain the pandemic outbreak, to name but a few. A significant contribution to their success comes from the computer science and information technology communities, both in support to other disciplines and as the primary driver of solutions for, e.g., diagnostics, social distancing, and contact tracing. In this work, we surveyed the Italian computer science and engineering community initiatives against the Covid19 pandemic. The 128 responses thus collected document the response of such a community during the first pandemic wave in Italy (February-May 2020), through several initiatives carried out by both single researchers and research groups able to promptly react to Covid19, even remotely. The data obtained by the survey are here reported, discussed and further investigated by Natural Language Processing techniques, to generate semantic clusters based on embedding representations of the surveyed activity descriptions. The resulting clusters have been then used to extend an existing Covid19 taxonomy with the classification of related research activities in computer science and information technology areas, summarizing this work contribution through a reproducible survey-to-taxonomy methodology

Functional Mixed Membership Models

Mixed membership models, or partial membership models, are a flexible unsupervised learning method that allows each observation to belong to multiple clusters. In this paper, we propose a Bayesian mixed membership model for functional data. By using the multivariate Karhunen-Lo\`eve theorem, we are able to derive a scalable representation of Gaussian processes that maintains data-driven learning of the covariance structure. Within this framework, we establish conditional posterior consistency given a known feature allocation matrix. Compared to previous work on mixed membership models, our proposal allows for increased modeling flexibility, with the benefit of a directly interpretable mean and covariance structure. Our work is motivated by studies in functional brain imaging through electroencephalography (EEG) of children with autism spectrum disorder (ASD). In this context, our work formalizes the clinical notion of "spectrum" in terms of feature membership proportions.Comment: 77 pages, 16 figure

Inhibition of Larval Development of Marine Copepods Acartia tonsa by Neonocotinoids

Neonicotinoids (NEOs) are neurotoxic pesticides widely used in agriculture due to their high effectiveness against pest insects. Despite their widespread use, very little is known about their toxicity towards marine organisms, including sensitive and ecologically relevant taxa such as copepods. Thus, we investigated the toxicity of five widely used NEOs, including acetamiprid (ACE), clothianidin (CLO), imidacloprid (IMI), thiacloprid (THI), and thiamethoxam (TMX), to assess their ability to inhibit the larval development of the copepod Acartia tonsa. The more toxic NEOs were ACE (EC50 = 0.73 μg L−1), TMX (EC50 = 1.71 μg L−1) and CLO (EC50 = 1.90 μg L−1), while the less toxic compound was IMI (EC50 = 8.84 μg L−1). Early life-stage mortality was unaffected by NEOs at all of the tested concentrations. The calculated toxicity data indicated that significant effects due to ACE (EC20 = 0.12 μg L−1), THI (EC20 = 0.88 μg L−1) and TMX (EC20 = 0.18 μg L−1) are observed at concentrations lower than established chronic aquatic life benchmarks reported by USEPA for freshwater invertebrates. Nevertheless, since environmental concentrations of NEOs are generally lower than the threshold concentrations we calculated for A. tonsa, the effects may be currently of concern only in estuaries receiving wastewater discharges or experiencing intense runoff from agricultur

Comparative transcriptome analysis of stylar canal cells identifies novel candidate genes implicated in the self-incompatibility response of Citrus clementina

<p>Abstract</p> <p>Background</p> <p>Reproductive biology in citrus is still poorly understood. Although in recent years several efforts have been made to study pollen-pistil interaction and self-incompatibility, little information is available about the molecular mechanisms regulating these processes. Here we report the identification of candidate genes involved in pollen-pistil interaction and self-incompatibility in clementine (<it>Citrus clementina </it>Hort. ex Tan.). These genes have been identified comparing the transcriptomes of laser-microdissected stylar canal cells (SCC) isolated from two genotypes differing for self-incompatibility response ('Comune', a self-incompatible cultivar and 'Monreal', a self- compatible mutation of 'Comune').</p> <p>Results</p> <p>The transcriptome profiling of SCC indicated that the differential regulation of few specific, mostly uncharacterized transcripts is associated with the breakdown of self-incompatibility in 'Monreal'. Among them, a novel F-box gene showed a drastic up-regulation both in laser microdissected stylar canal cells and in self-pollinated whole styles with stigmas of 'Comune' in concomitance with the arrest of pollen tube growth. Moreover, we identify a non-characterized gene family as closely associated to the self-incompatibility genetic program activated in 'Comune'. Three different aspartic-acid rich (Asp-rich) protein genes, located in tandem in the clementine genome, were over-represented in the transcriptome of 'Comune'. These genes are tightly linked to a DELLA gene, previously found to be up-regulated in the self-incompatible genotype during pollen-pistil interaction.</p> <p>Conclusion</p> <p>The highly specific transcriptome survey of the stylar canal cells identified novel genes which have not been previously associated with self-pollen rejection in citrus and in other plant species. Bioinformatic and transcriptional analyses suggested that the mutation leading to self-compatibility in 'Monreal' affected the expression of non-homologous genes located in a restricted genome region. Also, we hypothesize that the Asp-rich protein genes may act as Ca²⁺"entrapping" proteins, potentially regulating Ca²⁺homeostasis during self-pollen recognition.</p

Impact of sleep disorders on behavioral issues in preschoolers with autism spectrum disorder

BackgroundSleep disorders are one of the most common problems in children with Autism Spectrum Disorder (ASD). However, they often tend to be underdiagnosed and incorrectly treated in clinical practice. This study aims to identify sleep disorders in preschool children with ASD and to explore their relationship with the core symptoms of autism, the child's developmental and cognitive level as well as the psychiatric comorbidities. MethodsWe recruited 163 preschool children with a diagnosis of ASD. The Children's Sleep Habits Questionnaire (CSHQ) assessed sleep conditions. Multiple standardized tests were used to evaluate intellectual abilities, the presence of repetitive behaviors (through the Repetitive Behavior Scale-Revised), as well as the emotional-behavioral problems and the psychiatric comorbidities (through the Child Behavior Checklist -CBCL 1(1/2)-5). ResultsThe results showed that poor disorders had consistently higher scores in all areas assessed by the CSHQ and on the CBCL across all domains. The correlational analysis showed that severe sleep disorders were associated with higher scores in internalizing, externalizing, and total problems at the CBCL syndromic scales, and in all DSM-oriented CBCL subscales. Moreover, we found that the association between sleep disorders and restricted and repetitive behaviors (RRBs) is explained by the anxiety-related symptoms. ConclusionBased on these findings, the study recommends that screening for sleep problems followed by early intervention should constitute a routine part of clinical practice for children with ASD

IT-Covid19-IT: la risposta della comunità informatica italiana alla pandemia

La pandemia Covid19 ha avuto un forte impatto sulle nostre vite, anche da accademici. Ne è scaturita una reazione veemente della comunità scientifica i cui risultati sono sotto gli occhi di tutti: vaccini, terapie più puntuali ed efficaci, politiche di contenimento mirate, etc. A tutto ciò, l’informatica ha contribuito in maniera determinante, spesso con funzioni di supporto e servizio alle altre discipline, talvolta in primo piano con applicazioni specifiche, per esempio, per il distanziamento sociale ed il tracciamento dei contatti. Questo articolo prova a fare una fotografia della reazione della comunità informatica italiana alla pandemia Covid19, elaborando i dati ottenuti da un censimento condotto nel maggio 2020, a seguito della prima ondata, dalla Task Force Covid19-IT istituita allo scopo dal CINI (Consorzio Interuniversitario Nazionale per l’Informatica). I dati ottenuti dalle 131 proposte censite raccontano di una risposta decisa ed articolata della comunità, nata spontaneamente da centinaia di iniziative autonome distribuite su tutto il territorio nazionale e che deve proseguire, magari evolvendo in forme più organizzate