1,722,566 research outputs found
Applicazioni di metodologie statistiche e tecniche neuronali in merceologia: un confronto
No full textThe subjective duration of audiovisual looming and receding stimuli
No full textLooming visual stimuli (log-increasing in proximal size over time) and auditory stimuli (of increasing sound intensity over time) have been shown to be perceived as longer than receding visual and auditory stimuli (i. e., looming stimuli reversed in time). Here, we investigated whether such asymmetry in subjective duration also occurs for audiovisual looming and receding stimuli, as well as for stationary stimuli (i. e., stimuli that do not change in size and/or intensity over time). Our results showed a great temporal asymmetry in audition but a null asymmetry in vision. In contrast, the asymmetry in audiovision was moderate, suggesting that multisensory percepts arise from the integration of unimodal percepts in a maximum-likelihood fashion. © 2012 Psychonomic Society, Inc
SEMgsa: topology-based pathway enrichment analysis with structural equation models
No full textBackground: Pathway enrichment analysis is extensively used in high-throughput experimental studies to gain insight into the functional roles of pre-defined subsets of genes, proteins and metabolites. Methods that leverages information on the topology of the underlying pathways outperform simpler methods that only consider pathway membership, leading to improved performance. Among all the proposed software tools, there's the need to combine high statistical power together with a user-friendly framework, making it difficult to choose the best method for a particular experimental environment.Results: We propose SEMgsa, a topology-based algorithm developed into the framework of structural equation models. SEMgsa combine the SEM p values regarding node-specific group effect estimates in terms of activation or inhibition, after statistically controlling biological relations among genes within pathways. We used SEMgsa to identify biologically relevant results in a Coronavirus disease (COVID-19) RNA-seq dataset (GEO accession: GSE172114) together with a frontotemporal dementia (FTD) DNA methylation dataset (GEO accession: GSE53740) and compared its performance with some existing methods. SEMgsa is highly sensitive to the pathways designed for the specific disease, showing low p values ( < 0.001) and ranking in high positions, outperforming existing software tools. Three pathway dysregulation mechanisms were used to generate simulated expression data and evaluate the performance of methods in terms of type I error followed by their statistical power. Simulation results confirm best overall performance of SEMgsa.Conclusions: SEMgsa is a novel yet powerful method for identifying enrichment with regard to gene expression data. It takes into account topological information and exploits pathway perturbation statistics to reveal biological information. SEMgsa is implemented in the R package SEMgraph, easily available at https://CRAN.R-project. org/package=SEMgraph
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Vite (Il)legali. Immigrati africani in Italia e Portogallo
No full textLa questione degli immigrati “illegali” è oggi al centro del dibattito pubblico non solo europeo. Ma che cosa si intende esattamente per “illegalità” in contesti migratori? Come viene costruita, rappresentata e prodotta dai vari attori sociali, dalle istituzioni e dai mass media? In questo libro ci proponiamo di mettere in luce tali cruciali questioni attraverso l’analisi dei risultati di una ricerca interdisciplinare, focalizzata sulle pratiche e i vissuti di alcuni migranti provenienti da diversi paesi dell’Africa e sulle rappresentazioni e percezioni che essi producono dell’illegalità. Sulla base di un lavoro etnografico multi-situato, in Italia e in Portogallo, il testo si propone di rivisitare il concetto di legalità/illegalità nei dei due paesi presi in esame, anche secondo un’ottica di genere, mettendo in luce gli spazi di agency dei migranti senza documenti e facendo dialogare i diversi contesti dove “l’illegalità” si gioca: spazi di vita e pratiche quotidiane, legislazione sulla migrazione, rappresentazioni mediatiche
Conclusioni
No full textLa questione degli immigrati “illegali” è oggi al centro del dibattito pubblico non solo europeo. Ma che cosa si intende esattamente per “illegalità” in contesti migratori? Come viene costruita, rappresentata e prodotta dai vari attori sociali, dalle istituzioni e dai mass media? In questo libro ci proponiamo di mettere in luce tali cruciali questioni attraverso l’analisi dei risultati di una ricerca interdisciplinare, focalizzata sulle pratiche e i vissuti di alcuni migranti provenienti da diversi paesi dell’Africa e sulle rappresentazioni e percezioni che essi producono dell’illegalità. Sulla base di un lavoro etnografico multi-situato, in Italia e in Portogallo, il testo si propone di rivisitare il concetto di legalità/illegalità nei dei due paesi presi in esame, anche secondo un’ottica di genere, mettendo in luce gli spazi di agency dei migranti senza documenti e facendo dialogare i diversi contesti dove “l’illegalità” si gioca: spazi di vita e pratiche quotidiane, legislazione sulla migrazione, rappresentazioni mediatiche
SEMtree: tree-based structure learning methods with structural equation models
No full textMotivation: With the exponential growth of expression and protein-protein interaction (PPI) data, the identification of functional modules in PPI networks that show striking changes in molecular activity or phenotypic signatures becomes of particular interest to reveal process-specific information that is correlated with cellular or disease states. This requires both the identification of network nodes with reliability scores and the availability of an efficient technique to locate the network regions with the highest scores. In the literature, a number of heuristic methods have been suggested. We propose SEMtree(), a set of tree-based structure discovery algorithms, combining graph and statistically interpretable parameters together with a user-friendly R package based on structural equation models framework. Results: Condition-specific changes from differential expression and gene-gene co-expression are recovered with statistical testing of node, directed edge, and directed path difference between groups. In the end, from a list of seed (i.e. disease) genes or gene P-values, the perturbed modules with undirected edges are generated with five state-of-the-art active subnetwork detection methods. The latter are supplied to causal additive trees based on Chu-Liu-Edmonds' algorithm (Chow and Liu, Approximating discrete probability distributions with dependence trees. IEEE Trans Inform Theory 1968;14:462-7) in SEMtree() to be converted in directed trees. This conversion allows to compare the methods in terms of directed active subnetworks. We applied SEMtree() to both Coronavirus disease (COVID-19) RNA-seq dataset (GEO accession: GSE172114) and simulated datasets with various differential expression patterns. Compared to existing methods, SEMtree() is able to capture biologically relevant subnetworks with simple visualization of directed paths, good perturbation extraction, and classifier performance. Availability and implementation: SEMtree() function is implemented in the R package SEMgraph, easily available at https://CRAN.R-project.org/package=SEMgraph
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