From garbage to product and service systems: A longitudinal Finnish case study of waste management evolution.

This longitudinal case study analyses the development of the pioneering waste management (WM) system in the Vaasa region of Western Finland, since the late 1980s to the present. It reflects the general features of the evolving WM from the one-bag system and throwaway culture towards today's circular economy and product service systems. The Vaasa region is an excellent example of how WM has evolved in Finland, which also follows the main direction of travel in Europe.

Simulation-based assessments of fire emergency preparedness and response in virtual reality.

The current study aimed at evaluating the prospects of a three-dimensional gas power plant (GPP) simulation in an immersive virtual reality (IVR) environment for fire emergency preparedness and response (EPR). To achieve this aim, the study assessed the possibility of safety situational awareness, evacuation drills and hazard mitigation exercises during a fire emergency simulation scenario. The study likewise evaluated the safety and ergonomics of the environment while addressing this aim.

Sampling Rate Effects on Resting State fMRI Metrics.

Low image sampling rates used in resting state functional magnetic resonance imaging (rs-fMRI) may cause aliasing of the cardiorespiratory pulsations over the very low frequency (VLF) BOLD signal fluctuations which reflects to functional connectivity (FC). In this study, we examine the effect of sampling rate on currently used rs-fMRI FC metrics. Ultra-fast fMRI magnetic resonance encephalography (MREG) data, sampled with TR 0.

Combined spatiotemporal ICA (stICA) for continuous and dynamic lag structure analysis of MREG data.

This study investigated lag structure in the resting-state fMRI by applying a novel independent component (ICA) method to magnetic resonance encephalography (MREG) data. Briefly, the spatial ICA (sICA) was used for defining the frontal and back nodes of the default mode network (DMN), and the temporal ICA (tICA), which is enabled by the high temporal resolution of MREG (TR=100ms), was used to separate both neuronal and physiological components of these two spatial map regions. Subsequently, lag structure was investigated between the frontal (DMNvmpf) and posterior (DMNpcc) DMN nodes using both conventional method with all-time points and a sliding-window approach.

Synchronous multiscale neuroimaging environment for critically sampled physiological analysis of brain function: hepta-scan concept.

Functional connectivity of the resting-state networks of the brain is thought to be mediated by very-low-frequency fluctuations (VLFFs <0.1 Hz) in neuronal activity. However, vasomotor waves and cardiorespiratory pulsations influence indirect measures of brain function, such as the functional magnetic resonance imaging blood-oxygen-level-dependent (BOLD) signal.

Preoperative localization of the sensorimotor area using independent component analysis of resting-state fMRI.

Analysis of resting-state functional magnetic resonance imaging (fMRI) data is based on detecting low-frequency signal fluctuations in functionally connected brain areas. These synchronous fluctuations in resting-state networks have been observed in several studies with healthy subjects. In this study, we explored if independent component analysis (ICA) can be used to localize the sensorimotor area from resting-state fMRI data in patients with brain tumors.