Depth model building by constrained magnetotelluric inversion

In this paper we describe an approach aimed at integrating seismic and magnetotelluric data in a complex geological setting, characterised by thrust structures, in Southern Apennine, Southern Italy. Seismic data were collected by the «Global Offset» technique that is designed to record hight fold data in a wide range of offsets, without losing the benefit of near vertical reflection seismic. First arrivals picked from short to long offsets and the main reflections were inverted in order to produce a tomographic velocity-interface model. It was converted into a resistivity section applying an empirical relationship, obtained by well logs, between resistivity and velocity. That section was used as a reliable reference model for 2D inversion of magnetotelluric data collected along a parallel section very close to the seismic profile. The process was iterative and interactive and was aimed at producing consistent velocity and resistivity sections, honouring seismic and MT data set. The final MT model fits very well the observed apparent resistivity and phase, reproduces the main geological trends and its constrained by a well drilled close to the line

Factors associated with involuntary hospitalisation for psychiatric patients in Switzerland: a retrospective study.

Despite the scarce evidence for patients' benefits of coercion and its well-documented negative effects, the use of compulsion is still very common around Europe, with important variations among different countries. These variations have been partially explained by the different legal frameworks, but also by several individual-related, system-related and area-related characteristics, identified as predictors of the use of coercive measures. This study aimed to compare the socio-demographic and clinical profile as well as the referral and hospitalisation process of people voluntarily and involuntarily hospitalized in order to identify which factors could be associated with the use of coercion. All psychiatric admissions occurred between the 1st January 2015 and the 31st December 2015 were included in this retrospective study (n = 5027). The whole sample was split into two subgroups accordingly to the hospitalisation legal status at admission (voluntary vs involuntary) and differences between the two groups were examined. In order to identify the factors associated with coercion, all the variables reaching a p < .01 level of significance when comparing the two groups were included as independent variables into a multivariate logistic regression model. Globally, 62% of the admissions were voluntary and 38% were involuntary. Compared to the voluntary group, involuntary patients were significantly older, more frequently widowed and living in one specific district, and had a main diagnosis of schizophrenia (F20-F29) or organic mental disorders (F00-F09). People affected by organic mental disorders (F00-F09), with higher levels of psychotic symptoms, aggression and problems with medication adherence, were more likely to be involuntarily admitted. Moreover, living in District 1, being referred by a general practitioner, a general hospital or a psychiatric hospital and being involuntarily admitted during the previous 12 months, was associated with a higher risk of coercion. This study identified several individual-related, as well as system-related factors associated with the use of coercion. These results allowed us to trace a clearer profile of high-risk patients and to provide several inputs that could help local authorities, professionals and researchers to develop better-targeted alternative interventions reducing the use of coercion

Intensive Case Management for Addiction to promote engagement with care of people with severe mental and substance use disorders: an observational study.

Co-occurring severe mental and substance use disorders are associated with physical, psychological and social complications such as homelessness and unemployment. People with severe mental and substance use disorders are difficult to engage with care. The lack of treatment worsens their health and social conditions and increases treatment costs, as emergency department visits arise. Case management has proved to be effective in promoting engagement with care of people with severe mental and substance use disorders. However, this impact seemed mainly related to the case management model. The Intensive Case Management for Addiction (ICMA) aimed to improve engagement with care of people with severe mental and substance use disorders, insufficiently engaged with standard treatment. This innovative multidisciplinary mobile team programme combined Assertive Community Treatment and Critical Time Intervention methodologies. The aim of the study was to observe the impact of ICMA upon service use, treatment adherence and quality of support networks. Participants' psychosocial and mental functioning, and substance use were also assessed throughout the intervention. The study was observational. Eligible participants were all the people entering the programme during the first year of implementation (April 2014-April 2015). Data were collected through structured questionnaires and medical charts. Assessments were conducted at baseline and at 12 months follow-up or at the end of the programme if completed earlier. McNemar-Bowker's Test, General Linear Model repeated-measures analysis of variance and non-parametric Wilcoxon Signed Rank tests were used for the analysis. A total of 30 participants took part in the study. Results showed a significant reduction in the number of participants visiting the general emergency department compared to baseline. A significantly decreased number of psychiatric emergency department visits was also registered. Moreover, at follow-up participants improved significantly their treatment adherence, clinical status, social functioning, and substance intake and frequency of use. These promising results highlight the efficacy of the ICMA. The intervention improved engagement with care and the psychosocial situation of people with severe mental and substance use disorders, with consequent direct impact on their substance misuse

3D Modeling of the Magnetization of Superconducting Rectangular-Based Bulks and Tape Stacks

In recent years, numerical models have become popular and powerful tools to investigate the electromagnetic behavior of superconductors. One domain where this advances are most necessary is the 3D modeling of the electromagnetic behavior of superconductors. For this purpose, a benchmark problem consisting of superconducting cube subjected to an AC magnetic field perpendicular to one of its faces has been recently defined and successfully solved. In this work, a situation more relevant for applications is investigated: a superconducting parallelepiped bulk with the magnetic field parallel to two of its faces and making an angle with the other one without and with a further constraint on the possible directions of the current. The latter constraint can be used to model the magnetization of a stack of high-temperature superconductor tapes, which are electrically insulated in one direction. For the present study three different numerical approaches are used: the Minimum Electro-Magnetic Entropy Production (MEMEP) method, the $H$-formulation of Maxwell's equations and the Volume Integral Method (VIM) for 3D eddy currents computation. The results in terms of current density profiles and energy dissipation are compared, and the differences in the two situations of unconstrained and constrained current flow are pointed out. In addition, various technical issues related to the 3D modeling of superconductors are discussed and information about the computational effort required by each model is provided. This works constitutes a concrete result of the collaborative effort taking place within the HTS numerical modeling community and will hopefully serve as a stepping stone for future joint investigations

Low Energy STEM of Multi-Layers and Dopant Profiles

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Predicting involuntary hospitalization in psychiatry: A machine learning investigation.

Coercion in psychiatry is a controversial issue. Identifying its predictors and their interaction using traditional statistical methods is difficult, given the large number of variables involved. The purpose of this study was to use machine-learning (ML) models to identify socio-demographic, clinical and procedural characteristics that predict the use of compulsory admission on a large sample of psychiatric patients. We retrospectively analyzed the routinely collected data of all psychiatric admissions that occurred between 2013 and 2017 in the canton of Vaud, Switzerland (N = 25,584). The main predictors of involuntary hospitalization were identified using two ML algorithms: Classification and Regression Tree (CART) and Random Forests (RFs). Their predictive power was compared with that obtained through traditional logistic regression. Sensitivity analyses were also performed and missing data were imputed through multiple imputation using chain equations. The three models achieved similar predictive balanced accuracy, ranging between 68 and 72%. CART showed the lowest predictive power (68%) but the most parsimonious model, allowing to estimate the probability of being involuntarily admitted with only three checks: aggressive behaviors, who referred the patient to hospital and primary diagnosis. The results of CART and RFs on the imputed data were almost identical to those obtained on the original data, confirming the robustness of our models. Identifying predictors of coercion is essential to efficiently target the development of professional training, preventive strategies and alternative interventions. ML methodologies could offer new effective tools to achieve this goal, providing accurate but simple models that could be used in clinical practice

(Ti,Sn) solid solution-based gas sensors for new monitoring of hydraulic oil degradation

The proper operation of a fluid power system in terms of efficiency and reliability is directly related to the fluid state; therefore, the monitoring of fluid ageing in real time is fundamental to prevent machine failures. For this aim, an innovative methodology based on fluid vapor analysis through metal oxide (shortened: MOX) gas sensors has been developed. Two apparatuses were designed and realized: (i) a dedicated test bench to fast-age the fluid under controlled conditions; (ii) a laboratory MOX sensor system to test the headspace of the aged fluid samples. To prepare the set of MOX gas sensors suitable to detect the analytes’ concentrations in the fluid headspace, different functional materials were synthesized in the form of nanopowders, characterizing them by electron microscopy and X-ray diffraction. The powders were deposited through screen-printing technology, realizing thick-film gas sensors on which dynamical responses in the presence of the fluid headspace were obtained. It resulted that gas sensors based on solid solution TixSn1–xO2 with x = 0.9 and 0.5 offered the best responses toward the fluid headspace with lower response and recovery times. Furthermore, a decrease in the responses (for all sensors) with fluid ageing was observed

Mental health professionals' feelings and attitudes towards coercion.

Despite absence of clear evidence to assert that the use of coercion in psychiatry is practically and clinically helpful or effective, coercive measures are widely used. Current practices seem to be based on institutional cultures and decision-makers' attitudes towards coercion rather than led by recommendations issued from the scientific literature. Therefore, the main goal of our study was to describe mental health professionals' feelings and attitudes towards coercion and the professionals' characteristics associated with them. Mental health professionals working in the Department of Psychiatry of Lausanne University Hospital, Switzerland, were invited to participate to an online survey. A questionnaire explored participants' sociodemographic characteristics, professional background and current working context, and their feelings and attitudes towards coercion. Exploratory Structural Equation Modelling (ESEM) was used to determine the structure of mental health professionals' feelings and attitudes towards coercion and to estimate to which extent sociodemographic and professional characteristics could predict their underlying dimensions. 130 mental health professionals completed the survey. Even if a large number considered coercion a violation of fundamental rights, an important percentage of them agreed that coercion was nevertheless indispensable in psychiatry and beneficial to the patients. ESEM revealed that professionals' feelings and attitudes towards coercion could be described by four main dimensions labelled "Internal pressure", "Emotional impact", "External pressure" and "Relational involvement". The personal as well as the professional proximity with people suffering from mental disorders influences professionals' feeling and attitudes towards coercion. As voices recommend the end of coercion in psychiatry and despite the lack of scientific evidence, many mental health professionals remain convinced that it is a requisite tool beneficial to the patients. Clinical approaches that enhance shared decision making and give the opportunity to patients and professionals to share their experience and feelings towards coercion and thus alleviate stress among them should be fostered and developed