FedCohesion: Federated Identity Management in the Marche Region

Federated identity management is a set of technologies and processes supporting dynamically distribute identity information. Its adoption in Public Administrations maintains organizations autonomy giving at the same time citizens support to access the services that are distributed across security domains. In this paper, we propose the Marche Region experience for what concern federate identity management focusing on the regional authentication framework, named FedCohesion. It is bases on Security Assertion Markup Language standard and it results from Cohesion re-engineering. It is the old style legacy authentication framework. We first present resulting architecture showing supported identification process and pilot applications. Lessons learned and opportunities have been also presented

Intraperitoneal drain placement and outcomes after elective colorectal surgery: international matched, prospective, cohort study

Despite current guidelines, intraperitoneal drain placement after elective colorectal surgery remains widespread. Drains were not associated with earlier detection of intraperitoneal collections, but were associated with prolonged hospital stay and increased risk of surgical-site infections.Background Many surgeons routinely place intraperitoneal drains after elective colorectal surgery. However, enhanced recovery after surgery guidelines recommend against their routine use owing to a lack of clear clinical benefit. This study aimed to describe international variation in intraperitoneal drain placement and the safety of this practice. Methods COMPASS (COMPlicAted intra-abdominal collectionS after colorectal Surgery) was a prospective, international, cohort study which enrolled consecutive adults undergoing elective colorectal surgery (February to March 2020). The primary outcome was the rate of intraperitoneal drain placement. Secondary outcomes included: rate and time to diagnosis of postoperative intraperitoneal collections; rate of surgical site infections (SSIs); time to discharge; and 30-day major postoperative complications (Clavien-Dindo grade at least III). After propensity score matching, multivariable logistic regression and Cox proportional hazards regression were used to estimate the independent association of the secondary outcomes with drain placement. Results Overall, 1805 patients from 22 countries were included (798 women, 44.2 per cent; median age 67.0 years). The drain insertion rate was 51.9 per cent (937 patients). After matching, drains were not associated with reduced rates (odds ratio (OR) 1.33, 95 per cent c.i. 0.79 to 2.23; P = 0.287) or earlier detection (hazard ratio (HR) 0.87, 0.33 to 2.31; P = 0.780) of collections. Although not associated with worse major postoperative complications (OR 1.09, 0.68 to 1.75; P = 0.709), drains were associated with delayed hospital discharge (HR 0.58, 0.52 to 0.66; P < 0.001) and an increased risk of SSIs (OR 2.47, 1.50 to 4.05; P < 0.001). Conclusion Intraperitoneal drain placement after elective colorectal surgery is not associated with earlier detection of postoperative collections, but prolongs hospital stay and increases SSI risk

CyberBrain: A preliminary experience on non human primate

The study of abnormal electrical activity of the brain, such as epilepsy, is attracting more and more interest for its wide impact on the population. Intracranial EEG recording (electrocorticogaphy; EcoG) and direct cortical stimulation (DCS) are, nowadays, the most accurate and reliable techniques to map cortical function and to identify the boundaries of an epileptic focus. In this work we present the preliminary testing of intra-operative ECoG and DCS performed in a non-human primate using a new custom-made fully-implantable wireless 16- channels device (Patent Number: WO2012143850), called ECOGW-16E. This fully-integrated device, housed in a compact hermetically sealed Polyetheretherketone (PEEK) enclosure, exploits the newly available Medical Implant Communication Service band (MICS: 402-405 MHz). ECOGW-16E is wirelessly rechargeable using a special designed cage for recharge, developed in accordance with guidelines for accommodation of animals by Council of Europe

SPECTRE: a deep learning network for posture recognition in manufacturing

Work-related musculoskeletal disorders are a very impactful problem, both socially and economically, in the manufacturing sector. To control their effect, standardised methods and technologies for ergonomic assessment have been developed. The main technologies used are inertial sensors and vision-based systems. The former are accurate and reliable, but invasive and not affordable for many companies. The latter use machine learning algorithms to detect human pose and assess ergonomic risks. In this paper, using data collecting by reproducing the working environment in LUBE, the major Italian kitchen manufacturer, we propose SPECTRE (Sensor-independent Parallel dEep ConvoluTional leaRning nEtwork): a fully sensor-independent learning model based on convolutional networks to classify postures in the workplace. This system assesses ergonomic risks in major body segments through Deep Learning with a minimal impact. SPECTRE's performance is evaluated using established metrics for imbalanced data (precision, recall, F1-score and area under the precision-recall curve). Overall, SPECTRE shows good performance and, thanks to an agnostic explainable machine learning method, is able to extrapolate which patterns are significant in the input