Informal sport is central to Finnish children’s leisure and physical activity time. This paper aims to build a better understanding of the travel time-based accessibility to informal sports ...facilities, specifically to ice skating fields, for children and adolescents (aged 7–19) in the city of Helsinki. We focused on the winter of 2020–2021 because COVID-19 restrictions on indoor activities resulted in ice skating fields being among the few public facilities that could remain open. Additionally, the weather was favourable for maintaining outdoor ice skating fields. We analysed if there would be a difference in children’s independent travel times by public transport or walking to ice skating fields due to the COVID-19 pandemic related recommendations by Helsinki Region Transport to avoid public transport. Children in Finland usually travel to and from school independently. Hence we focused on the transition from public transport to walking and omitted car usage, which would require an adult. We also looked at the potential differences in travel time to ice skating fields by analysing different types of fields separately. This difference would be of significance if climate change resulted in warmer winters in Finland. Helsinki has two types of ice skating fields: naturally frozen and mechanically frozen, of which only the mechanically frozen fields would be used during a warmer winter that is above zero degrees Celsius. We took a geographic information systems (GIS) analysis approach using travel time and population catchments. The study’s main findings show that during a milder winter and by walking, the accessibility for children is greatly reduced to 55.2%; that is, children face an increased travel time when naturally frozen ice skating fields are not in use. However, almost 100% of the child population can access both types of fields within a travel time of 30 minutes by public transport.
Background Hippocampal volume loss on magnetic resonance imaging (MRI) has been reported in patients with depression. It is uncertain whether a small hippocampus renders a person vulnerable to ...develop depression or whether it is a consequence of depression. In this study, we addressed whether smaller baseline MRI hippocampal volumes increase the risk of incident depression. We also examined whether depressive symptoms at baseline were associated with decline in hippocampal volume during follow-up. Methods Data were obtained in a prospective population-based study over a 10-year period. A sample of 514 nondemented persons aged 60 to 90 years underwent baseline measurements in 1995–1996 including three-dimensional MRI scans for assessment of hippocampal volumes and depressive symptoms (measured with Center for Epidemiologic Studies Depression Scale). Follow-up MRIs were made in 1999–2000 and in 2006. Incident depression was identified through standardized psychiatric examinations and continuous monitoring of medical and pharmaceutical records. Results During a mean follow-up of 6.8 years per person (range .07–10.01 years), 135 of the 514 persons developed a clinically relevant episode of incident depressive symptoms. There was no association between baseline hippocampal volumes and incident depression (hazard ratio per SD decrease of average hippocampal volume .98 .81–1.19, p = .84). A baseline Center for Epidemiologic Studies Depression Scale score of 16 or higher predicted a faster rate of decline in hippocampal volume. Also, incident depression was accompanied by a faster decline in left hippocampal volume. Conclusions This study provides no evidence that a small hippocampal volume precedes the development of late-life depression. Depression, however, may lead to a faster rate of hippocampal volume decline.
Since hippocampal volume has been found to be an early biomarker for Alzheimer's disease, there is large interest in automated methods to accurately, robustly, and reproducibly extract the ...hippocampus from MRI data. In this work we present a segmentation method based on the minimization of an energy functional with intensity and prior terms, which are derived from manually labelled training images. The intensity energy is based on a statistical intensity model that is learned from the training images. The prior energy consists of a spatial and regularity term. The spatial prior is obtained from a probabilistic atlas created by registering the training images to the unlabelled target image, and deforming and averaging the training labels. The regularity prior energy encourages smooth segmentations. The resulting energy functional is globally minimized using graph cuts. The method was evaluated using image data from a population-based study on diseases among the elderly. Two set of images were used: a small set of 20 manually labelled MR images and a larger set of 498 images, for which manual volume measurements were available, but no segmentations. This data was previously used in a volumetry study that found significant associations between hippocampal volume and cognitive decline and incidence of dementia. Cross-validation experiments with the labelled set showed similarity indices of 0.852 and 0.864 and mean surface distances of 0.40 and 0.36 mm for the left and right hippocampus. 83% of the automated segmentations of the large set were rated as ‘good’ by a trained observer. Also, the proposed method was used to repeat the manual hippocampal volumetry study. The automatically obtained hippocampal volumes showed significant associations with cognitive decline and dementia, similar to the manually measured volumes. Finally, direct quantitative and qualitative comparisons showed that the proposed method outperforms a multi-atlas based segmentation method.
Scientific research increasingly focuses on visual symptoms of people with Parkinson's disease (PD). However, this mostly involves functional measures, whereas self-reported data are equally ...important for guiding clinical care.
This review provides an overview of the nature and prevalence of self-reported visual complaints by people with PD, compared to healthy controls.
A systematic literature search was performed. Studies from three databases (PubMed, PsycInfo, and Web of Science) were screened for eligibility. Only studies that reported results of visual self-reports in people with idiopathic PD were included.
One hundred and thirty-nine eligible articles were analyzed. Visual complaints ranged from function-related complaints (e.g., blurred vision, double vision, increased sensitivity to light or changes in contrast sensitivity) to activity-related complaints (e.g., difficulty reading, reaching, or driving). Visual complaints were more prevalent in people with PD compared to healthy controls. The presence of visual complaints leads to a reduced quality of life (QoL). Increased prevalence and severity of visual complaints in people with PD are related to longer disease duration, higher disease severity, and off-state.
A large proportion of people with PD have visual complaints, which negatively affect QoL. Complaints are diverse in nature, and specific and active questioning by clinicians is advised to foster timely recognition, acknowledgement, and management of these complaints.
A variety of international actors, such as the UN and NATO, intervene in complex environments, such as Afghanistan. In order to overcome complexity and for 'us' to deal with 'them', constructs such ...as 'the insurgents' and 'the government' are used to help 'our' understanding and to simplify the picture. Subsequently, these constructs become subject to nation building and counterinsurgency theories applied by the 'international community'. Many of these are suboptimal because their subjects were constructs in the first place. The result is a shadow boxing match, in which international policies dissolve in local realities. On the basis of social psychology theories, this paper develops the hypothesis that in complex peacebuilding environments decision-makers structure and simplify disorder, which leads to suboptimal interventions, to which local actors respond in a process of friction. This hypothesis is tested on the case of Afghanistan.
Accurate automated brain structure segmentation methods facilitate the analysis of large-scale neuroimaging studies. This work describes a novel method for brain structure segmentation in magnetic ...resonance images that combines information about a structure's location and appearance. The spatial model is implemented by registering multiple atlas images to the target image and creating a spatial probability map. The structure's appearance is modeled by a classifier based on Gaussian scale-space features. These components are combined with a regularization term in a Bayesian framework that is globally optimized using graph cuts. The incorporation of the appearance model enables the method to segment structures with complex intensity distributions and increases its robustness against errors in the spatial model. The method is tested in cross-validation experiments on two datasets acquired with different magnetic resonance sequences, in which the hippocampus and cerebellum were segmented by an expert. Furthermore, the method is compared to two other segmentation techniques that were applied to the same data. Results show that the atlas- and appearance-based method produces accurate results with mean Dice similarity indices of 0.95 for the cerebellum, and 0.87 for the hippocampus. This was comparable to or better than the other methods, whereas the proposed technique is more widely applicable and robust.
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