Biotimer assay: A reliable and rapid method for the evaluation of central venous catheter microbial colonization

Adherent bacteria and biofilm frequently colonize central venous catheters (CVCs). CVC colonization is correlated to infections and particularly to bloodstream ones. The classical microbiological methods to determine of CVC colonization are not fully reliable and are time-consuming. BioTimer Assay (BTA) is a biological method already used to count bacteria adherent to abiotic surfaces and biofilm without sample manipulation. BTA employs specific reagents whose color changed according to bacterial metabolism. BTA is based on the principle that a metabolic reaction will be faster when more bacteria are present in the sample. Therefore, the time required for color changes of BTA reagents determines the number of bacteria present in the sample through a correlation line. Here, for the first time, we applied BTA and a specifically developed laboratory procedure to evaluate CVC colonization in comparison with the routine microbiological method (RMM). 125 CVCs removed from patients for suspected catheter-related bloodstream infection (CRBSI) or at hospital discharge were examined. BTA was reliable in assessing sterility and CVC colonization (100% agreement with RMM) and in recognizing the presence of fermenting or non-fermenting bacteria (97.1% agreement with RMM) shortening the analytical time by between 2- and 3-fold. Moreover, the reliability of BTA as early alert of CRBSI was evaluated. The sensitivity, specificity, positive, and negative predictive values for BTA as an early alert of CRBSI were 100, 40.0, 88.8 and 100%, respectively. In conclusion, BTA and the related laboratory procedure should be incorporated into routine microbiological methods since it can be considered a reliable tool to evaluate CVC colonization in a very short time and a rapid alert for CRBSIs

Battery Aging-Aware Online Optimal Control: An Energy Management System for Hybrid Electric Vehicles Supported by a Bio-Inspired Velocity Prediction

In this manuscript, we address the problem of online optimal control for torque splitting in hybrid electric vehicles that minimises fuel consumption and preserves battery life. We divide the problem into the prediction of the future velocity profile (i.e. driver intention estimation) and the online optimal control of the hybrid powertrain following a Model Predictive Control (MPC) scheme. The velocity prediction is based on a bio-inspired driver model, which is compared on various datasets with two alternative prediction algorithms adopted in the literature. The online optimal control problem addresses both the fuel consumption and the preservation of the battery life using an equivalent cost given the estimated speed profile (i.e. guaranteeing the desired performance). The battery degradation is evaluated by means of a state-of-the-art electrochemical model. Both the predictor and the Energy Management System (EMS) are evaluated in simulation using real driving data divided into 30 driving cycles from 10 drivers characterised by different driving styles. A comparison of the EMS performances is carried out on two different benchmarks based on an offline optimization, in one case on the entire dataset length and in the second on an ideal prediction using two different receding horizon lengths. The proposed online system, composed of the velocity prediction algorithm and the optimal control MPC scheme, shows comparable performances with the previous ideal benchmarks in terms of fuel consumption and battery life preservation. The simulations show that the online approach is able to significantly reduce the capacity loss of the battery, while preserving the fuel saving performances

Cooperative Safety Applications for C-ITS Equipped and Non-equipped Vehicles Supported by an Extended Local Dynamic Map built on SAFE STRIP Technology

The work describes the contribution of SAFESTRIP EU project technology to the implementation of the Dynamic Local Map used by C-ITS safety applications. The road strips developed in SAFESTRIP are able to detect and estimate the longitudinal and lateral position of detected vehicle at lane level. This is exploited by many existing and new C-ITS applications. Here a Coorperative Intersection Support application is described and used as example to explain the concept and highlight the benefit put forward by the road strips informations

Cooperation between Roads and Vehicles: Field Validation of a Novel Infrastructure-Based Solution for All Road Users’ Safety

Cooperative intelligent transport systems (C-ITS) are expected to considerably influence road safety, traffic efficiency and comfort. Nevertheless, their market penetration is still limited, on the one hand due to the high costs of installation and maintenance of the infrastructures and, on the other hand, due to the price of support automated driving functions. A breakthrough C-ITS technological solution was studied, designed, built and tested that is based on the implementation of custom low-cost on-road platforms (named “strips”) that embed micro/nano sensors, communication technologies and energy harvesting to shift intelligence from the vehicle to the road infrastructure. The strips, through a V2X and LTE communication gateway, transmit real-time, reliable and accurate information at lane level about the environmental and road condition, the traffic and the other road users’ position and speed. The exchanged information supports a series of C-ITS functions and services extending equipped vehicles capabilities and providing similar functions to non-equipped ones (including powered two wheelers). The general framework and the technological solution proposed is presented and the results of the field trials, conducted in three pilot sites around Europe, quantify the promising system performance as well as the positive effects of the C-ITS applications developed and tested on driver/rider’s behavior