Recent technological advances enable the collection of intensive longitudinal data. This scoping review aimed to provide an overview of methods for collecting intensive time series data in mental health research as well as basic principles, current applications, target constructs, and statistical methods for this type of data.

In January 2021, the database MEDLINE was searched. Original articles were identified that (1) used active or passive data collection methods to gather intensive longitudinal data in daily life, (2) had a minimum sample size of N ⩾ 100 participants, and (3) included individuals with subclinical or clinical mental health problems.

In total, 3799 original articles were identified, of which 174 met inclusion criteria. The most widely used methods were diary techniques (e.g. Experience Sampling Methodology), various types of sensors (e.g. accelerometer), and app usage data. Target constructs included affect, various symptom domains, cognitive processes, sleep, dysfunctional behaviour, physical activity, and social media use. There was strong evidence on feasibility of, and high compliance with, active and passive data collection methods in diverse clinical settings and groups. Study designs, sampling schedules, and measures varied considerably across studies, limiting the generalisability of findings.

Gathering intensive longitudinal data has significant potential to advance mental health research. However, more methodological research is required to establish and meet critical quality standards in this rapidly evolving field. Advanced approaches such as digital phenotyping, ecological momentary interventions, and machine-learning methods will be required to efficiently use intensive longitudinal data and deliver personalised digital interventions and services for improving public mental health.

This paper gives an overview of the low-complexity radio frequency microelectromechanical systems (RF MEMS) switch concept and technology of EADS Innovation Works in Germany. Starting in 2003, a capacitive switch concept, which is unique in several aspects, was developed to address specific needs in the aeronautic and space. Thermally grown silicon oxide as dielectric layer, the silicon substrate as actuation electrode, and a conductive zone realized by ion implantation make the EADS RF MEMS switch a very simple, low-cost, and reliable approach. In this document, data on experimental investigations are presented, which demonstrate outstanding performance figures in terms of insertion loss, isolation, frequency range, bandwidth, RF-power handling, and robustness with respect to thermal load. Based on this concept, numerous different circuits in particular single-pole single-throws (SPSTs), single-pole multi-throws (SPMTs), tunable filters, phase shifters, and electronically steerable antennas between 6 and 100 GHz have been designed, fabricated, and characterized.

An efficient utilization of the sun spectrum is a key issue in the field of thin-film silicon solar cell technology. Therefore, different strategies for enhanced light absorption were presented in the last years. In order to achieve a better understanding of light scattering at nanotextured interfaces the optical properties of a large variety of samples were studied. The angle resolved scattering behavior was analyzed by means of a developed ray tracing model. As an alternative to randomly textured substrates, the influence of periodically textured substrates on the light propagation in solar cells was experimentally and numerically studied with respect to improved light in-coupling and light trapping. Based on a deeper understanding a new tandem cell structure with a diffractive element between the top and bottom cell was developed. Finally, the influence of metallic nanoparticles on the cell performance was studied.

Oz is a multiparadigm language that supports logic programming as one of its major paradigms. A multiparadigm language is designed to support different programming paradigms (logic, functional, constraint, object-oriented, sequential, concurrent, etc.) with equal ease. This paper has two goals: to give a tutorial of logic programming in Oz; and to show how logic programming fits naturally into the wider context of multiparadigm programming. Our experience shows that there are two classes of problems, which we call algorithmic and search problems, for which logic programming can help formulate practical solutions. Algorithmic problems have known efficient algorithms. Search problems do not have known efficient algorithms but can be solved with search. The Oz support for logic programming targets these two problem classes specifically, using the concepts needed for each. This is in contrast to the Prolog approach, which targets both classes with one set of concepts, which results in less than optimal support for each class. We give examples that can be run interactively on the Mozart system, which implements Oz. To explain the essential difference between algorithmic and search programs, we define the Oz execution model. This model subsumes both concurrent logic programming (committed-choice-style) and search-based logic programming (Prolog-style). Furthermore, as consequences of its multiparadigm nature, the model supports new abilities such as first-class top levels, deep guards, active objects, and sophisticated control of the search process. Instead of Horn clause syntax, Oz has a simple, fully compositional, higher-order syntax that accommodates the abilities of the language. We give a brief history of Oz that traces the development of its main ideas and we summarize the lessons learned from this work. Finally, we give many entry points into the Oz literature.

A simple mechanical stirring process leads to charge-stabilised dispersions of aligned, substrate-grown, CVD-grown multi-wall carbon nanotubes in an epoxy resin. Subsequent sample processing, after the addition of the hardener, can be used to induce the nanotube agglomeration necessary to achieve electrically conductive bulk composites at low loading fractions. Both the nanotube percolation threshold and the resulting bulk conductivity can be adjusted by selection of suitable processing parameters and nanotube aspect ratio. This behaviour of aligned CVD-grown multi-wall carbon nanotubes allows lower electrical percolation thresholds than are possible with entangled multi-wall carbon nanotubes, single-wall carbon nanotube bundles, or carbon black in an epoxy matrix. Furthermore, the application of electric fields during composite processing induces the formation of aligned multi-wall carbon nanotube networks between electrodes dipped into the dispersion. Such composites show an electrical conductivity above the anti-static level and retain a degree of optical transmissivity.

Macroscopic poly(ether ether ketone) (PEEK) and polypropylene (PP) nanocomposites containing vapour-grown carbon nanofibres (CNF) were produced using standard polymer processing. Tensile tests revealed a linear increase in composite stiffness with nanofibre content. A detailed DSC study verified that under standard processing conditions the degree of crystallinity and the crystalline structure of these semicrystalline thermoplastics were not affected by the nanofibres. Nevertheless, we provide evidence that the nanoscale filler can alter the polymer morphology under certain conditions, an effect which needs to be considered when evaluating nanocomposite properties. Given the absence of morphological changes in the standard nanocomposites we were able to calculate the intrinsic nanofibre modulus using short fibre theory; both distinctively different matrix systems show a similar effective nanofibre modulus.