SQL versus NoSQL Databases for Geospatial Applications

In the last years, we are witnessing an increasing availability of geolocated data, ranging from satellite images to user generated content (e.g., tweets). This big amount of data is exploited by several cloud-based applications to deliver effective and customized services to end users. In order to provide a good user experience, a low-latency response time is needed, both when data are retrieved and provided. To achieve this goal, current geospatial applications need to exploit efficient and scalable geospatial databases, the choice of which has a high impact on the overall performance of the deployed applications. In this paper, we compare, from a qualitative point of view, four state-of-the-art SQL and NoSQL databases with geospatial features, and then we analyze the performances of two of them, selecting the ones based on the Database-as-a-service (DBaaS) model: Azure SQL Database and Azure DocumentDB (i.e., an SQL database versus a NoSQL one). The empirical evaluation shows pros and cons of both solutions and it is performed on a real use case related to an emergency management application

abCDEuropa: guida al wiki dei CDE italiani

Il wiki dei CDE italiani è uno strumento pensato e creato specificamente per l’uso online poiché ha una struttura reticolare di rimandi incrociati invece di un’esposizione lineare. Questa breve guida non intende quindi riproporre il wiki dei CDE, che è uno strumento dinamico in continua evoluzione e aggiornamento, bensì fornire in una pluralità di supporti oltre al web - carta, libro elettronico - indicazioni generali e sintetiche sui principali contenuti del wiki

Preface of the 31st Italian Symposium on Advanced Database Systems

This volume contains the proceedings of the 31st Italian Symposium on Advanced Database Systems (SEBD - Sistemi Evoluti per Basi di Dati), held in Galzinagno Terme (Padua, Italy) from 2 to 5 July 2023.</p

Preface of the 31st Italian Symposium on Advanced Database Systems

This volume contains the proceedings of the 31st Italian Symposium on Advanced Database Systems (SEBD - Sistemi Evoluti per Basi di Dati), held in Galzinagno Terme (Padua, Italy) from 2 to 5 July 2023.</p

Association between atrial fibrillation and <i>Helicobacter pylori</i>

The connection between atrial fibrillation (AF) and H. pylori (HP) infection is still matter of debate. We performed a systematic review and metanalysis of studies reporting the association between AF and HF. A systematic review of all available reports in literature of the incidence of HP infection in AF and comparing this incidence with subjects without AF were analysed. Risk ratio and 95% confidence interval (CI) and risk difference with standard error (SE) were the main statistics indexes. Six retrospective studies including a total of 2921 were included at the end of the selection process. Nine hundred-fifty-six patients (32.7%) were in AF, whereas 1965 (67.3%) were in normal sinus rhythm (NSR). Overall, 335 of 956 patients with AF were HP positive (35%), whereas 621 were HP negative (65%). In addition, 643 of 1965 NSR patients (32.7%) were HP positive while 1,322 were negative (67.3%; Chi-square 2.15, p = 0.21). The Cumulative Risk Ratio for AF patients for developing an HP infection was 1.19 (95% CI 1.08–1.41). In addition, a small difference risk towards AF was found (0.11 [SE = 0.04]). Moreover, neither RR nor risk difference were influenced by the geographic area at meta-regression analysis. Finally, there was a weak correlation between AF and HP (coefficient = 0.04 [95% CI −0.01–0.08]). We failed to find any significant correlation between H. pylori infection and AF and, based on our data, it seems unlikely than HP can be considered a risk factor for AF. Further larger research is warranted

Association between convalescent plasma treatment and mortality in COVID-19: a collaborative systematic review and meta-analysis of randomized clinical trials.

Funder: laura and john arnold foundationBACKGROUND: Convalescent plasma has been widely used to treat COVID-19 and is under investigation in numerous randomized clinical trials, but results are publicly available only for a small number of trials. The objective of this study was to assess the benefits of convalescent plasma treatment compared to placebo or no treatment and all-cause mortality in patients with COVID-19, using data from all available randomized clinical trials, including unpublished and ongoing trials (Open Science Framework, https://doi.org/10.17605/OSF.IO/GEHFX ). METHODS: In this collaborative systematic review and meta-analysis, clinical trial registries (ClinicalTrials.gov, WHO International Clinical Trials Registry Platform), the Cochrane COVID-19 register, the LOVE database, and PubMed were searched until April 8, 2021. Investigators of trials registered by March 1, 2021, without published results were contacted via email. Eligible were ongoing, discontinued and completed randomized clinical trials that compared convalescent plasma with placebo or no treatment in COVID-19 patients, regardless of setting or treatment schedule. Aggregated mortality data were extracted from publications or provided by investigators of unpublished trials and combined using the Hartung-Knapp-Sidik-Jonkman random effects model. We investigated the contribution of unpublished trials to the overall evidence. RESULTS: A total of 16,477 patients were included in 33 trials (20 unpublished with 3190 patients, 13 published with 13,287 patients). 32 trials enrolled only hospitalized patients (including 3 with only intensive care unit patients). Risk of bias was low for 29/33 trials. Of 8495 patients who received convalescent plasma, 1997 died (23%), and of 7982 control patients, 1952 died (24%). The combined risk ratio for all-cause mortality was 0.97 (95% confidence interval: 0.92; 1.02) with between-study heterogeneity not beyond chance (I2 = 0%). The RECOVERY trial had 69.8% and the unpublished evidence 25.3% of the weight in the meta-analysis. CONCLUSIONS: Convalescent plasma treatment of patients with COVID-19 did not reduce all-cause mortality. These results provide strong evidence that convalescent plasma treatment for patients with COVID-19 should not be used outside of randomized trials. Evidence synthesis from collaborations among trial investigators can inform both evidence generation and evidence application in patient care

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Real-time object detection and tracking in mixed reality using Microsoft HoloLens

This paper presents a mixed reality system that, using the sensors mounted on the Microsoft Hololens headset and a cloud service, acquires and processes in real-time data to detect and track different kinds of objects and finally superimposes geographically coherent holographic texts on the detected objects. Such a goal has been achieved dealing with the intrinsic headset hardware limitations, by performing part of the overall computation in an edge/cloud environment. In particular, the heavier object detection algorithms, based on Deep Neural Networks (DNNs), are executed in the cloud. At the same time, we compensate for cloud transmission and computation latencies by running light scene detection and object tracking onboard the headset. The proposed pipeline allows meeting the real-time constraint by exploiting at the same time the power of state of art DNNs and the potential of Microsoft Hololens. This paper presents the design choices and describes the original algorithmic steps we devised to achieve real-time tracking in mixed reality. Finally, the proposed system is experimentally validated