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Background: PICC-ports may be defined as totally implantable central venous devices inserted in the upper limb using the current state-of-the-art techniques of PICC insertion (ultrasound-guided venipuncture of deep veins of the arm, micro-puncture kits, proper location of the tip preferably by intracavitary ECG), with placement of the reservoir at the middle third of the arm. A previous report on breast cancer patients demonstrated the safety and efficacy of these devices, with a very low failure rate. Methods: This retrospective multicenter cohort study—developed by GAVeCeLT (the Italian Group of Long-Term Venous Access Devices)—investigated the outcomes of PICC-ports in a large cohort of unselected patients. The study included 4480 adult patients who underwent PICC-port insertion in five Italian centers, during a period of 60 months. The primary outcome was device failure, defined as any serious adverse event (SAE) requiring removal. The secondary outcome was the incidence of temporary adverse events (TAE) not requiring removal. Results: The median follow-up was 15.5 months. Device failure occurred in 52 cases (1.2%), the main causes being local infection (n = 7; 0.16%) and CRBSI (n = 19; 0.42%). Symptomatic catheter-related thrombosis occurred in 93 cases (2.1%), but removal was required only in one case (0.02%). Early/immediate and late TAE occurred in 904 cases (20.2%) and in 176 cases (3.9%), respectively. Conclusions: PICC-ports are safe venous access devices that should be considered as an alternative option to traditional arm-ports and chest-ports when planning chemotherapy or other long-term intermittent intravenous treatments.

This paper considers the multi-vehicle automated driving coordination problem. We develop a distributed, hybrid decision-making framework for safe and efficient autonomous driving of selfish vehicles on multi-lane highways, where each dynamics is modeled as a mixed-logical–dynamical system. We formalize the coordination problem as a generalized mixed-integer potential game, seeking an equilibrium solution that generates almost individually optimal mixed-integer decisions, given the safety constraints. Finally, we embed the proposed best-response-based algorithms within the distributed open- and closed-loop control policies., Accepted Author Manuscript, Team DeSchutter

Study of the climate in the Mediterranean basin during different historical periods has taken on a particular importance, particularly regarding its role (together with other factors) in the evolution of human settlement patterns. Although the Roman age is traditionally considered a period with a favourable climate, recent studies have revealed considerable complexity in terms of regional climate variations. In this paper, we compare the hydrological change from speleothem proxy records with flood reconstructions from archaeological sites for Northern Tuscany (central Italy). We identify a period of oscillating climatic conditions culminating in a multidecadal dry event during the 1st century bc, followed by a century of increased precipitation at the beginning of the Roman Empire and subsequently a return to drier conditions in the 2nd century ad. The period of rainfall increase documented by the speleothems agrees with both the archaeological flood record as well as historical flood data available for the Tiber River, ca. 300 km to the south. These data also suggest a return to wetter conditions following the 3nd and 4rd centuries ad.

This paper proposes a decentralised explicit (closed-form) iterative formula that solves convex programming problems with linear equality constraints and interval bounds on the decision variables. In particular, we consider a team of decision agents, each setting the value of a subset of the variables, and a team of information agents, in charge of ensuring that the equality constraints are fulfilled. The structure of the constraint matrix imposes a communication pattern between decision and information agents, which can be represented as a bipartite graph. We associate each information agent with an integral variable and each decision agent with a saturated function, which takes the interval bounds into account, and we design a decentralised dynamic mechanism that globally converges to the optimal solution. Under mild conditions, the convergence is shown to be exponential. We also provide a discrete-time algorithm, based on the Euler system, and we give an upper bound for the step parameter to ensure convergence. Although the considered optimisation problem is static, we show that the proposed scheme can be successfully applied to find the optimal solution of network-decentralised dynamic control problems., Accepted Author Manuscript, Team Tamas Keviczky

Team DeSchutter