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The paper seeks to propose a specific approach based on Dynamic Analysis and Chaos Theory aiming to emphasize the differences into the eddy current signals obtained by related non‐destructive tests, when the inspected specimens have flaws with different shapes.

Non‐linear eddy current analysis is very useful for flaw detection in many in‐service inspections. State‐of‐the‐art technologies allow one to define position and depth of defects, but the shape identification is still an open problem. In this paper, experimental data have been subjected to a dynamical analysis in order to relate the trend of eddy current signals to the shape of analyzed defect.

In particular, a dynamical reconstruction by means of recurrence plots (RPs) has been carried out in order to detect analogies and differentiations between different eddy current signals. Moreover, cross‐correlation between RPs of a reference benchmark and testing eddy current signals has been applied in order to emphasize a different dynamical behaviour and to detect a particular flaw's shape. In this way, a real‐time algorithm for defect shape classification has been performed.

Proposed approach is very interesting, and it is an innovation in non‐destructive testing procedures. In fact, the shape identification of a flaw is still an open challenge. The proposed approach, based on dynamic analysis, gives the key to solve this particular ill‐posed problem, by introducing a relation between the eddy current measurements and the shape of defect existing in the inspected specimen. Very interesting preliminary results have been obtained.

Substance abuse is a major public health concern, with over millions of people suffering from it worldwide. Although there is an abundance of treatment options, many of these rehabilitative trajectories are subject to “drop-out”. In addition, “drop-out” is a significant risk factor for relapse. There is an urgent demand for effective treatment, which would enable patients to reduce abuse and prevent relapse. Takiwasi is an addiction treatment centre that combines traditional Amazonian plant medicine with conventional western medicine and psychotherapy. The purpose of this paper is to explore whether socio-demographics factors, such as education level and occupation, psychiatric comorbidities and primary drug use, are associated with treatment non-completion of Ayahuasca (AYA)-assisted addiction therapy.

Data on the first treatment episode of 121 patients were collected from the patient database from the years 2012 to 2017. To determine whether there is an association between the variables of interest and treatment non-completion, a χ² analysis and a logistic regression analysis were performed.

Of the 121 patients analysed, 48.2 per cent completed their treatment, whilst 51.8 per cent did not. Students compared to those who are employed showed significantly higher odds for treatment non-completion (p=0.006; OR=3.7; 95% CI=1.5–9.6). Other variables in the multivariable analysis showed no significant relationship with treatment non-completion. While several limitations restricted the study, the findings suggest that the AYA-assisted treatment in Takiwasi may benefit from additional support for patients who are students. Moreover, it is advised to conduct more long-term follow-up of patients in order to gain better insight into the outcome of treatment at an AYA-assisted treatment centre.

It appears that AYA-assisted therapy in a therapeutic community is a feasible type of treatment for addiction, for which further studies should elucidate the role of motivation in relation to socio-demographic factors and type of addiction in the risk of treatment non-completion.