PillCam COLON 2© in Crohn's disease: A new concept of pan-enteric mucosal healing assessment

AIM To evaluate mucosal healing in patients with small bowel plus colonic Crohn's disease (CD) with a single non-invasive examination, by using PillCam COLON 2 (PCC2). METHODS Patients with non-stricturing nonpenetrating small bowel plus colonic CD in sustained corticosteroid-free remission were included. At diagnosis, patients had undergone ileocolonoscopy to identify active CD lesions, such as ulcers and erosions, and small bowel capsule endoscopy to assess the Lewis Score (LS). After = 1 year of follow-up, patients underwent entire gastrointestinal tract evaluation with PCC2. The primary endpoint was assessment of CD mucosal healing, defined as no active colonic CD lesions and LS < 135. RESULTS Twelve patients were included (7 male; mean age: 32 years), and mean follow-up was 38 mo. The majority of patients (83.3%) received immunosuppressive therapy. Three patients (25%) achieved mucosal healing in both the small bowel and the colon, while disease activity was limited to either the small bowel or the colon in 5 patients (42%). It was possible to observe the entire gastrointestinal tract in 10 of the 12 patients (83%) who underwent PCC2. CONCLUSION Only three patients in sustained corticosteroid-free clinical remission achieved mucosal healing in both the small bowel and the colon, highlighting the limitations of clinical assessment when stratifying disease activity, and the need for pan-enteric endoscopy to guide therapeutic modification.

Continuous monitoring of concrete mechanical properties since an early age to support construction phasing

The assessment of concrete mechanical properties during construction of concrete structures is of paramount importance for many intrinsic operations. However many of the available non-destructive methods for mechanical properties have limitations for use in construction sites. One of such methodologies is EMM-ARM, which is a variant of classic resonant frequency methods. This paper aims to demonstrate the efforts towards in-situ applicability of EMMARM, as to provide real-time information about concrete mechanical properties such as E-modulus and compressive strength. To achieve the aforementioned objective, a set of adaptations to the method have been successfully implemented and tested: (i) the reduction of the beam span; (ii) the use of a different mould material and (iii) a new support system for the beams. Based on these adaptations, a reusable mould was designed to enable easier systematic use of EMMARM. A pilot test was successfully performed under in-situ conditions during a bridge construction.

A bayesian approach for NDT data fusion: The Saint Torcato Church case study

This paper presents a methodology based on the Bayesian data fusion techniques applied to non-destructive and destructive tests for the structural assessment of historical constructions. The aim of the methodology is to reduce the uncertainties of the parameter estimation. The Young's modulus of granite stones was chosen as an example for the present paper. The methodology considers several levels of uncertainty since the parameters of interest are considered random variables with random moments. A new concept of Trust Factor was introduced to affect the uncertainty related to each test results, translated by their standard deviation, depending on the higher or lower reliability of each test to predict a certain parameter.

Detection of dangerous situations using a smart internet of things system

The Internet of Things (IoT) is a concept that can foster the emergence of innovative applications. In order to minimize parents’s concerns about their children’s safety, this paper presents the design of a smart Internet of Things system for identifying dangerous situations. The system will be based on real time collection and analysis of physiological signals monitored by non-invasive and non-intrusive sensors, Frequency IDentification (RFID) tags and a Global Positioning System (GPS) to determine when a child is in danger. The assumption of a state of danger is made taking into account the validation of a certain number of biometric reactions to some specific situations and according to a self-learning algorithm developed for this architecture. The results of the analysis of data collected and the location of the child will be able in real time to child’s care holders in a web application.