Landscape and well-being: a scoping study on the health-promoting impact of outdoor environments

OBJECTIVES: The present literature review conceptualises landscape as a health resource that promotes physical, mental, and social well-being. Different health-promoting landscape characteristics are discussed. METHODS: This article is based on a scoping study which represents a special kind of qualitative literature review. Over 120 studies have been reviewed in a five-step-procedure, resulting in a heuristic device. RESULTS: A set of meaningful pathways that link landscape and health have been identified. Landscapes have the potential to promote mental well-being through attention restoration, stress reduction, and the evocation of positive emotions; physical well-being through the promotion of physical activity in daily life as well as leisure time and through walkable environments; and social well-being through social integration, social engagement and participation, and through social support and security. CONCLUSION: This scoping study allows us to systematically describe the potential of landscape as a resource for physical, mental and social well-being. A heuristic framework is presented that can be applied in future studies, facilitating systematic and focused research approaches and informing practical public health interventions.

[Evaluation of the "Schema-focused Emotive Behavioural Therapy" (SET) for Patients with Personality Disorders: Results of a Randomised Controlled Trial.]

The "Schema-focussed Emotive Behavioral Therapy" (SET) was developed by our research group as a new group therapy approach for patients with personality disorders from all clusters (A to C; DSM-IV). It was evaluated in a randomised controlled study (n = 93). Data were collected before and after treatment as well as one year after study entry. A completer analysis was conducted with matched subgroups (n = 60). After therapy, SET patients improved in the outcome domains interactional behavior, strain, and symptomatic complaints (IIP-D, GAF, VEV-VW, BSI-P). Furthermore, they showed a significant lower dropout rate. At the follow-up assessment, Cluster C patients of the experimental group deteriorated with regard to symptomatic complaints (BSI-P). In contrast, cluster B patients improved more over time compared to control subjects. SET seems to be an adequate and effective group therapy with effects that seem to be stable over time, especially for patients with Cluster B diagnosis.

LakeMIP Kivu: evaluating the representation of a large, deep tropical lake by a set of one-dimensional lake models

The African great lakes are of utmost importance for the local economy (fishing), as well as being essential to the survival of the local people. During the past decades, these lakes experienced fast changes in ecosystem structure and functioning, and their future evolution is a major concern. In this study, for the first time a set of one-dimensional lake models are evaluated for Lake Kivu (2.28°S; 28.98°E), East Africa. The unique limnology of this meromictic lake, with the importance of salinity and subsurface springs in a tropical high-altitude climate, presents a worthy challenge to the seven models involved in the Lake Model Intercomparison Project (LakeMIP). Meteorological observations from two automatic weather stations are used to drive the models, whereas a unique dataset, containing over 150 temperature profiles recorded since 2002, is used to assess the model’s performance. Simulations are performed over the freshwater layer only (60 m) and over the average lake depth (240 m), since salinity increases with depth below 60 m in Lake Kivu and some lake models do not account for the influence of salinity upon lake stratification. All models are able to reproduce the mixing seasonality in Lake Kivu, as well as the magnitude and seasonal cycle of the lake enthalpy change. Differences between the models can be ascribed to variations in the treatment of the radiative forcing and the computation of the turbulent heat fluxes. Fluctuations in wind velocity and solar radiation explain inter-annual variability of observed water column temperatures. The good agreement between the deep simulations and the observed meromictic stratification also shows that a subset of models is able to account for the salinity- and geothermal-induced effects upon deep-water stratification. Finally, based on the strengths and weaknesses discerned in this study, an informed choice of a one-dimensional lake model for a given research purpose becomes possible.

Well-being and learning in school

Although there are various definitions for the term “well-being,” it is agreed that well-being in school represents a set of subjective feelings and attitudes toward school. Moreover, enjoyment (some use the term “happiness”) is recognized as a core element of well-being in general as well as at school. Well-being in school is defined as an indicator of the quality of scholastic life, and contributes to students’ physical and psychological health and development. As such it is strongly connected to learning. Well-being in school consists of cognitive, emotional, and physical components, i.e., a learner’s thoughts, feelings, and bodily sensations. Consequently, it differs significantly from an individual’s cognitive appraisals like satisfaction, or from discrete positive emotions like enjoyment. Well-being in school can be described through the relationship of positive and negative aspects of school life

A Parametric Test of Perfect Ranking in Balanced Ranked Set Sampling

Many techniques based on data which are drawn by Ranked Set Sampling (RSS) scheme assume that the ranking of observations is perfect. Therefore it is essential to develop some methods for testing this assumption. In this article, we propose a parametric location-scale free test for assessing the assumption of perfect ranking. The results of a simulation study in two special cases of normal and exponential distributions indicate that the proposed test performs well in comparison with its leading competitors.

Measurement of the TeV atmospheric muon charge ratio with the complete OPERA data set

The OPERA detector, designed to search for νμ → ντ oscillations in the CNGS beam, is located in the underground Gran Sasso laboratory, a privileged location to study TeV-scale cosmic rays. For the analysis here presented, the detector was used to measure the atmospheric muon charge ratio in the TeV region. OPERA collected chargeseparated cosmic ray data between 2008 and 2012. More than 3 million atmospheric muon events were detected and reconstructed, among which about 110000 multiple muon bundles. The charge ratio Rμ ≡ Nμ+/Nμ− was measured separately for single and for multiple muon events. The analysis exploited the inversion of the magnet polarity which was performed on purpose during the 2012 Run. The combination of the two data sets with opposite magnet polarities allowedminimizing systematic uncertainties and reaching an accurate determination of the muon charge ratio. Data were fitted to obtain relevant parameters on the composition of primary cosmic rays and the associated kaon production in the forward fragmentation region. In the surface energy range 1–20 TeV investigated by OPERA, Rμ is well described by a parametric model including only pion and kaon contributions to themuon flux, showing no significant contribution of the prompt component. The energy independence supports the validity of Feynman scaling in the fragmentation region up to 200 TeV/nucleon primary energy.