Online Maintenance of Minimal Directed Hypergraphs

In this paper we deal with directed hypergraphs, a generalization of directed graphs previously introduced in the literature. In particular, we investigate the problem of maintaining efficiently information about minimal hyperpaths while new hyperarcs are inserted. We consider several definitions of minimal hyperpath and we prove that accordingly to some of such definitions the problem of finding the minimal hyperpath is NP-complete, while hyperpaths with minimal GAP and minimal RANK can be found in polynomial time. We deal with this problem in an online fashion, by allowing insertions of hyperarcs in the hypergraphs. We present data structures and algorithms which allow to return a hyperpath with minimal GAP or RANK between an arbitrarily given pair of nodes in a time which is linear in its size. The total time required to maintain the data structure during the insertion of new hyperarcs is (9(m n2) for min-GAP and (9(m n2 log n) for min-RANK (where m is the total size of the description of the hyperarcs and n is the number of nodes). These results are useful in applications where directed hypergraphs are known to be a suitable model (e.g. transition networks, rewriting systems, database schemes, logic programming and problem solving)

Risk Assessment for Venous Thromboembolism in Chemotherapy-Treated Ambulatory Cancer Patients: A Machine Learning Approach

OBJECTIVE: To design a precision medicine approach aimed at exploiting significant patterns in data, in order to produce venous thromboembolism (VTE) risk predictors for cancer outpatients that might be of advantage over the currently recommended model (Khorana score). DESIGN: Multiple kernel learning (MKL) based on support vector machines and random optimization (RO) models were used to produce VTE risk predictors (referred to as machine learning [ML]-RO) yielding the best classification performance over a training (3-fold cross-validation) and testing set. RESULTS: Attributes of the patient data set ( n = 1179) were clustered into 9 groups according to clinical significance. Our analysis produced 6 ML-RO models in the training set, which yielded better likelihood ratios (LRs) than baseline models. Of interest, the most significant LRs were observed in 2 ML-RO approaches not including the Khorana score (ML-RO-2: positive likelihood ratio [+LR] = 1.68, negative likelihood ratio [-LR] = 0.24; ML-RO-3: +LR = 1.64, -LR = 0.37). The enhanced performance of ML-RO approaches over the Khorana score was further confirmed by the analysis of the areas under the Precision-Recall curve (AUCPR), and the approaches were superior in the ML-RO approaches (best performances: ML-RO-2: AUCPR = 0.212; ML-RO-3-K: AUCPR = 0.146) compared with the Khorana score (AUCPR = 0.096). Of interest, the best-fitting model was ML-RO-2, in which blood lipids and body mass index/performance status retained the strongest weights, with a weaker association with tumor site/stage and drugs. CONCLUSIONS: Although the monocentric validation of the presented predictors might represent a limitation, these results demonstrate that a model based on MKL and RO may represent a novel methodological approach to derive VTE risk classifiers. Moreover, this study highlights the advantages of optimizing the relative importance of groups of clinical attributes in the selection of VTE risk predictors

COVID-19-Related Social Isolation Predispose to Problematic Internet and Online Video Gaming Use in Italy

COVID-19 pandemic and its related containment measures have been associated with increased levels of stress, anxiety and depression in the general population. While the use of digital media has been greatly promoted by national governments and international authorities to maintain social contacts and healthy lifestyle behaviors, its increased access may also bear the risk of inappropriate or excessive use of internet-related resources. The present study, part of the COVID Mental hEalth Trial (COMET) study, aims at investigating the possible relationship between social isolation, the use of digital resources and the development of their problematic use. A cross sectional survey was carried out to explore the prevalence of internet addiction, excessive use of social media, problematic video gaming and binge watching, during Italian phase II (May-June 2020) and III (June-September 2020) of the pandemic in 1385 individuals (62.5% female, mean age 32.5 +/- 12.9) mainly living in Central Italy (52.4%). Data were stratified according to phase II/III and three groups of Italian regions (northern, central and southern). Compared to the larger COMET study, most participants exhibited significant higher levels of severe-to-extremely-severe depressive symptoms (46.3% vs. 12.4%; p < 0.01) and extremely severe anxiety symptoms (77.8% vs. 7.5%; p < 0.01). We also observed a rise in problematic internet use and excessive gaming over time. Mediation analyses revealed that COVID-19-related general psychopathology, stress, anxiety, depression and social isolation play a significant role in the emergence of problematic internet use, social media addiction and problematic video gaming. Professional gamers and younger subjects emerged as sub-populations particularly at risk of developing digital addictions. If confirmed in larger and more homogenous samples, our findings may help in shedding light on possible preventive and treatment strategies for digital addictions

The effect of social media and infodemic on mental health during the COVID-19 pandemic: results from the COMET multicentric trial

On January 30, 2020, the World Health Organization (WHO) declared the status of pandemic due to the COVID-19 infection. The initial phases of the pandemic were characterized by uncertainty and public fears. In order to cope with such unexpected conditions, people adopted different coping strategies, including search for information, accessing Internet, and using social media. The present study based on the COMET collaborative research network aims to: (1) assess use of Internet and of social media among the Italian general population; (2) explore differences in web usage between people with pre-existing mental disorders and the general population; (3) identify changes over time in social media usage along the phase 1 of the pandemic; (4) identify the clinical, socio-demographic and contextual predictors of excessive use of social media. A significant increase in time spent on Internet, with an average time of 4.8  ±  0.02 h per day, was found in the global sample of 20,720 participants. Compared with the general population, Internet use was significantly higher in people with pre-existing mental disorders (5.2  ± 0.1 h vs. 4.9  ±  0.02; p < 0.005). According to the multivariate logistic regression model, the risk of excessive use of social media and Internet was significantly higher in people with moderate levels of depressive symptoms (OR: 1.26, CI 95%: 0.99 to 1.59, p < 0.0.005); while protective factors were being students (OR: 0.72, CI 95%: 0.53 to 0.96, p < 0.0029) and living in central Italy (OR: 0.46, CI 95%: 0.23 to 0.90, p < 0.002). The evaluation of social media and Internet use by the general population represents a first step for developing specific protective and supportive interventions for the general population, including practical suggestions on how to safely use Internet and social media

Linear Time Analysis of Properties of Conflict-Free and General Petri nets

We introduce the notion of T-path within Petri nets, and propose a simple approach, based on previous work developed for directed hypergraphs, in order to determine structural properties of nets; in particular, we study the relationships between T-paths in a Petri net and _rable sequences of transitions. Let us consider a net P = hP; T; A;M0i and the set of places with a positive marking in M0, i.e., P0 = fp j M0(p) > 0g. If we regard the net as a directed graph, the existence of a simple path from any place in P0 to a transition t is, of course, a necessary condition for the potential _rability of t. This is su_cient only if the net is a State Machine, where j_tj = jt_j = 1 for all t 2 T. In this paper we show that the existence of a T-path from any subset of P0 to a transition t is a more restrictive condition and is, again, a necessary condition for the potential _rability of t. But, in this case: (a) if P is a Conict Free Petri net, this is also a su_cient condition, (b) if P is a general Petri net, t is potentially _rable by increasing the number of tokens in P0. For Conict-Free nets (CFPN) we consider the following problems: (a) determining the set of _rable transitions, (b) determining the set of reachable places, (c) determining the set of live transitions, (d) deciding the boundedness of the net. For all these problems we provide algorithms requiring linear space and time, i.e., O(jAj + jPj + jTj), for a net P = hP; T; A;M0i. Previous results for this class of networks are given by Howell, Rosier and Yen [18], providing algorithms for solving problems in Conict-Free nets in O(jPj_jTj) time and space. Given a Petri net and a marking M, the well known coverability problem consists in _nding a reachable marking M0 such that M0 _ M; this problem is known to be EXPSPACE-hard [30]. For general Petri nets we provide a partial answer to this problem. M is coverable by augmentation if it is coverable from an augmented marking M00 of the initial marking M0: M00 _ M0 and, for all p 2 P, M00(p) = 0 if M0(p) = 0. We solve this problem in linear time. The algorithms to compute T-paths are incremental: it is possible to modify the network (adding new places, transitions, arcs, tokens), and update the set of potentially _rable transitions and reachable places without recomputing them from scratch

Fondamenti di basi di dati. Teoria, metodo ed esercizi

Questo testo tratta le basi di dati, senza particolari presupposti sulle conoscenze necessarie, cercando di avvicinare il lettore ai temi trattati con gradualità e con linguaggio intuitivo. Attraverso un percorso guidato, il testo si propone di fornire: una piena comprensione dei concetti e dei metodi fondamentali, un elevato grado di autosufficienza e capacità di autodocumentazione nell'uso di strumenti comunemente utilizzati nella pratica professionale, le basi per eventuali approfondimenti su testi più avanzati e/o tecnologie specifiche. Dopo l'introduzione dei concetti fondamentali, vengono trattati gli aspetti necessari alla comprensione, alla progettazione e allo sviluppo delle basi di dati: modello relazionale, linguaggio SQL, progetto mediante il modello Entità-Relazione, sistemi di gestione di basi di dati. Sono inclusi riferimenti ad alcuni recenti sviluppi del settore, nonché al trattamento delle collezioni dati, nei formati più usuali, anche attraverso linguaggi di programmazione. La trattazione è corredata di esempi e di riferimenti a contenuti disponibili sul sito di supporto