An Empirical Study on Budget-Aware Online Kernel Algorithms for Streams of Graphs

Kernel methods are considered an effective technique for on-line learning. Many approaches have been developed for compactly representing the dual solution of a kernel method when the problem imposes memory constraints. However, in literature no work is specifically tailored to streams of graphs. Motivated by the fact that the size of the feature space representation of many state-of-the-art graph kernels is relatively small and thus it is explicitly computable, we study whether executing kernel algorithms in the feature space can be more effective than the classical dual approach. We study three different algorithms and various strategies for managing the budget. Efficiency and efficacy of the proposed approaches are experimentally assessed on relatively large graph streams exhibiting concept drift. It turns out that, when strict memory budget constraints have to be enforced, working in feature space, given the current state of the art on graph kernels, is more than a viable alternative to dual approaches, both in terms of speed and classification performance.Comment: Author's version of the manuscript, to appear in Neurocomputing (ELSEVIER

A tree-based kernel for graphs with continuous attributes

The availability of graph data with node attributes that can be either discrete or real-valued is constantly increasing. While existing kernel methods are effective techniques for dealing with graphs having discrete node labels, their adaptation to non-discrete or continuous node attributes has been limited, mainly for computational issues. Recently, a few kernels especially tailored for this domain, and that trade predictive performance for computational efficiency, have been proposed. In this paper, we propose a graph kernel for complex and continuous nodes' attributes, whose features are tree structures extracted from specific graph visits. The kernel manages to keep the same complexity of state-of-the-art kernels while implicitly using a larger feature space. We further present an approximated variant of the kernel which reduces its complexity significantly. Experimental results obtained on six real-world datasets show that the kernel is the best performing one on most of them. Moreover, in most cases the approximated version reaches comparable performances to current state-of-the-art kernels in terms of classification accuracy while greatly shortening the running times.Comment: This work has been submitted to the IEEE Transactions on Neural Networks and Learning Systems for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Machine Learning and MADIT methodology for the fake news identification: the persuasion index

[EN] The phenomenon of fake news has grown concurrently with the rise of social networks that allow people to directly access news without the mediation of reliable sources. Recognizing news as fake is a difficult task for humans, and even tougher for a machine. This proposal aims to redesign the problem: from a check of truthfulness of news content, to the analysis of texts’ persuasion level. That is how information is introduced to the reader, assuming that fake news is aimed at persuading towards the reality of sense they intend to convey. M.A.D.I.T. methodology has been chosen. It is useful to describe how texts are built, overcoming the content/structure analysis level and stressing the study of Discursive Repertories: discursive modalities of reality of sense building, classified into real and fake news categories thanks to the Machine learning application. For the dataset building 7,387 news have been analysed. The results highlight different profiles of text building between the two groups: the different and typical discursive repertories allow to validate the methodological approach as a good predictor of the persuasion level of texts, not only of news, but also of information in domains such as the economic financial one (e.g. GameStop event).Orrù, L.; Moro, C.; Cuccarini, M.; Paita, M.; Dalla Riva, MS.; Bassi, D.; Da San Martino, G.... (2022). Machine Learning and MADIT methodology for the fake news identification: the persuasion index. En 4th International Conference on Advanced Research Methods and Analytics (CARMA 2022). Editorial Universitat Politècnica de València. 165-172. https://doi.org/10.4995/CARMA2022.2022.1508116517

On Babylonian lavatories and sewers

This study begins by examining the archaeological and documentary evidence for lavatories (toilets) and foul-water drains in ancient Mesopotamian dwelling houses. It goes on to investigate the use, etymology and history of the Akkadian word asurrû: in the Old Babylonian period it served mainly as a term for a kind of foul-water drain or “sewer” but later shed that meaning

Management of acute diverticulitis with pericolic free gas (ADIFAS). an international multicenter observational study

Background: There are no specific recommendations regarding the optimal management of this group of patients. The World Society of Emergency Surgery suggested a nonoperative strategy with antibiotic therapy, but this was a weak recommendation. This study aims to identify the optimal management of patients with acute diverticulitis (AD) presenting with pericolic free air with or without pericolic fluid. Methods: A multicenter, prospective, international study of patients diagnosed with AD and pericolic-free air with or without pericolic free fluid at a computed tomography (CT) scan between May 2020 and June 2021 was included. Patients were excluded if they had intra-abdominal distant free air, an abscess, generalized peritonitis, or less than a 1-year follow-up. The primary outcome was the rate of failure of nonoperative management within the index admission. Secondary outcomes included the rate of failure of nonoperative management within the first year and risk factors for failure. Results: A total of 810 patients were recruited across 69 European and South American centers; 744 patients (92%) were treated nonoperatively, and 66 (8%) underwent immediate surgery. Baseline characteristics were similar between groups. Hinchey II-IV on diagnostic imaging was the only independent risk factor for surgical intervention during index admission (odds ratios: 12.5, 95% CI: 2.4-64, P =0.003). Among patients treated nonoperatively, at index admission, 697 (94%) patients were discharged without any complications, 35 (4.7%) required emergency surgery, and 12 (1.6%) percutaneous drainage. Free pericolic fluid on CT scan was associated with a higher risk of failure of nonoperative management (odds ratios: 4.9, 95% CI: 1.2-19.9, P =0.023), with 88% of success compared to 96% without free fluid ( P <0.001). The rate of treatment failure with nonoperative management during the first year of follow-up was 16.5%. Conclusion: Patients with AD presenting with pericolic free gas can be successfully managed nonoperatively in the vast majority of cases. Patients with both free pericolic gas and free pericolic fluid on a CT scan are at a higher risk of failing nonoperative management and require closer observation

Evolving trends in the management of acute appendicitis during COVID-19 waves. The ACIE appy II study

Background: In 2020, ACIE Appy study showed that COVID-19 pandemic heavily affected the management of patients with acute appendicitis (AA) worldwide, with an increased rate of non-operative management (NOM) strategies and a trend toward open surgery due to concern of virus transmission by laparoscopy and controversial recommendations on this issue. The aim of this study was to survey again the same group of surgeons to assess if any difference in management attitudes of AA had occurred in the later stages of the outbreak. Methods: From August 15 to September 30, 2021, an online questionnaire was sent to all 709 participants of the ACIE Appy study. The questionnaire included questions on personal protective equipment (PPE), local policies and screening for SARS-CoV-2 infection, NOM, surgical approach and disease presentations in 2021. The results were compared with the results from the previous study. Results: A total of 476 answers were collected (response rate 67.1%). Screening policies were significatively improved with most patients screened regardless of symptoms (89.5% vs. 37.4%) with PCR and antigenic test as the preferred test (74.1% vs. 26.3%). More patients tested positive before surgery and commercial systems were the preferred ones to filter smoke plumes during laparoscopy. Laparoscopic appendicectomy was the first option in the treatment of AA, with a declined use of NOM. Conclusion: Management of AA has improved in the last waves of pandemic. Increased evidence regarding SARS-COV-2 infection along with a timely healthcare systems response has been translated into tailored attitudes and a better care for patients with AA worldwide

The Biodiversity of the Mediterranean Sea: Estimates, Patterns, and Threats

The Mediterranean Sea is a marine biodiversity hot spot. Here we combined an extensive literature analysis with expert opinions to update publicly available estimates of major taxa in this marine ecosystem and to revise and update several species lists. We also assessed overall spatial and temporal patterns of species diversity and identified major changes and threats. Our results listed approximately 17,000 marine species occurring in the Mediterranean Sea. However, our estimates of marine diversity are still incomplete as yet—undescribed species will be added in the future. Diversity for microbes is substantially underestimated, and the deep-sea areas and portions of the southern and eastern region are still poorly known. In addition, the invasion of alien species is a crucial factor that will continue to change the biodiversity of the Mediterranean, mainly in its eastern basin that can spread rapidly northwards and westwards due to the warming of the Mediterranean Sea. Spatial patterns showed a general decrease in biodiversity from northwestern to southeastern regions following a gradient of production, with some exceptions and caution due to gaps in our knowledge of the biota along the southern and eastern rims. Biodiversity was also generally higher in coastal areas and continental shelves, and decreases with depth. Temporal trends indicated that overexploitation and habitat loss have been the main human drivers of historical changes in biodiversity. At present, habitat loss and degradation, followed by fishing impacts, pollution, climate change, eutrophication, and the establishment of alien species are the most important threats and affect the greatest number of taxonomic groups. All these impacts are expected to grow in importance in the future, especially climate change and habitat degradation. The spatial identification of hot spots highlighted the ecological importance of most of the western Mediterranean shelves (and in particular, the Strait of Gibraltar and the adjacent Alboran Sea), western African coast, the Adriatic, and the Aegean Sea, which show high concentrations of endangered, threatened, or vulnerable species. The Levantine Basin, severely impacted by the invasion of species, is endangered as well