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Strong winds induced by extratropical storms cause a large number of power outages, especially in highly forested countries such as Finland. Thus, predicting the impact of the storms is one of the key challenges for power grid operators. This article introduces a novel method to predict the storm severity for the power grid employing ERA5 reanalysis data combined with forest inventory. We start by identifying storm objects from wind gust and pressure fields by using contour lines of 15 m s−1 and 1000 hPa, respectively. The storm objects are then tracked and characterized with features derived from surface weather parameters and forest vegetation information. Finally, objects are classified with a supervised machine-learning method based on how much damage to the power grid they are expected to cause. Random forest classifiers, support vector classifiers, naïve Bayes processes, Gaussian processes, and multilayer perceptrons were evaluated for the classification task, with support vector classifiers providing the best results.

Most existing models for estimating electric system impacts from windstorms tend to have detailed representation only for the electric or only for the meteorological system. As a result, there is little evidence on how models with detailed electric systems and realistic wind gust field representations would perform in different windstorm cases. This work explores the evidence for the ability of such a fragility-based model to generate realistic spatiotemporal lost load profiles for the most impactful windstorm cases in Finland. The literature review shows multiple driving factors for windstorm impacts that are difficult to assess analytically, and similarities between the most impactful windstorms. All the available interruption data for thirteen years were analyzed, with their grouping by individual storm and calm periods. The fixing of time distribution fits for these periods show most faults as being within the 20% uncertainty bounds of the severity-dependent distribution trendlines. The medium-voltage electricity grid impact model with national coverage was applied for the three most impactful and most recent windstorm cases, with the model calibrated for one case. The generated spatiotemporal lost load profiles in all cases recreate historic profiles within the similar error margins of approximately 20%.

Adenosine, its interacting A 1 and A 2A receptors, and particularly the variant rs5751876 in the A 2A gene ADORA2A have been shown to modulate anxiety, arousal, and sleep. In a pilot positron emission tomography (PET) study in healthy male subjects, we suggested an effect of rs5751876 on in vivo brain A 1 receptor (A 1 AR) availability. As female sex and adenosinergic/dopaminergic interaction partners might have an impact on this rs5751876 effect on A 1 AR availability, we aimed to (1) further investigate the pilot male-based findings in an independent, newly recruited cohort including women and (2) analyze potential modulation of this rs5751876 effect by additional adenosinergic/dopaminergic gene variation. Healthy volunteers (32/11 males/females) underwent phenotypic characterization including self-reported sleep and A 1 AR-specific quantitative PET. Rs5751876 and 31 gene variants of adenosine A 1 , A 2A , A 2B , and A 3 receptors, adenosine deaminase, and dopamine D 2 receptor were genotyped. Multivariate analysis revealed an rs5751876 effect on A 1 AR availability ( P  = 0.047), post hoc confirmed in 30 of 31 brain regions (false discovery rate (FDR) corrected P values < 0.05), but statistically stronger in anxiety-related regions (e.g., amygdala, hippocampus). Additional effects of ADORA1 rs1874142 were identified; under its influence rs5751876 and rs5751876 × sleep had strengthened effects on A 1 AR availability ( P both  < 0.02; post hoc FDR-corrected P s < 0.05 for 29/30 regions, respectively). Our results support the relationship between rs5751876 and A 1 AR availability. Additional impact of rs1874142, together with rs5751876 and sleep, might be involved in regulating arousal and thus the development of mental disorders like anxiety disorders. The interplay of further detected suggestive ADORA2A × DRD2 interaction, however, necessitates larger future samples more comparable to magnetic resonance imaging (MRI)-based samples.

Background Bio-logging and animal tracking datasets continuously grow in volume and complexity, documenting animal behaviour and ecology in unprecedented extent and detail, but greatly increasing the challenge of extracting knowledge from the data obtained. A large variety of analysis methods are being developed, many of which in effect are inaccessible to potential users, because they remain unpublished, depend on proprietary software or require significant coding skills. Results We developed MoveApps, an open analysis platform for animal tracking data, to make sophisticated analytical tools accessible to a global community of movement ecologists and wildlife managers. As part of the Movebank ecosystem, MoveApps allows users to design and share workflows composed of analysis modules (Apps) that access and analyse tracking data. Users browse Apps, build workflows, customise parameters, execute analyses and access results through an intuitive web-based interface. Apps, coded in R or other programming languages, have been developed by the MoveApps team and can be contributed by anyone developing analysis code. They become available to all user of the platform. To allow long-term and cross-system reproducibility, Apps have public source code and are compiled and run in Docker containers that form the basis of a serverless cloud computing system. To support reproducible science and help contributors document and benefit from their efforts, workflows of Apps can be shared, published and archived with DOIs in the Movebank Data Repository. The platform was beta launched in spring 2021 and currently contains 49 Apps that are used by 316 registered users. We illustrate its use through two workflows that (1) provide a daily report on active tag deployments and (2) segment and map migratory movements. Conclusions The MoveApps platform is meant to empower the community to supply, exchange and use analysis code in an intuitive environment that allows fast and traceable results and feedback. By bringing together analytical experts developing movement analysis methods and code with those in need of tools to explore, answer questions and inform decisions based on data they collect, we intend to increase the pace of knowledge generation and integration to match the huge growth rate in bio-logging data acquisition.

This study proposes a role-playing experiment to explore the value of modern impact-based weather forecasts on the decision-making process to (i) issue warnings and manage the official emergency response under uncertainty and (ii) communicate and trigger protective action at different levels of the warning system across Europe. Here, flood or strong-wind game simulations seek to represent the players' realistic uncertainties and dilemmas embedded in the real-time forecasting-warning processes. The game was first tested in two scientific workshops in Finland and France, where European researchers, developers, forecasters and civil protection representatives played the simulations. Two other game sessions were organized afterwards (i) with undergraduate university students in France and (ii) with Finnish stakeholders involved in the management of hazardous weather emergencies. First results indicate that multi-model developments and crowdsourcing tools increase the level of confidence in the decision-making under pressure. We found that the role-playing approach facilitates interdisciplinary cooperation and argumentation on emergency response in a fun and interactive manner. The ANYCaRE experiment was proposed, therefore, as a valuable learning tool to enhance participants' understanding of the complexities and challenges met by various actors in weather-related emergency management.

This study investigates the impacts of extratropical cyclones on Finland's electricity grids, focusing on 92 significant windstorms from 2005 to 2018. We present a classification method for extratropical cyclones based on the arrival location and direction. Rather than using meteorological criteria to identify windstorms, we select them based on their impacts, namely the number of power outages, to reach a more targeted understanding of windstorm impacts compared to traditional approaches. Key findings indicate that south-west-originating windstorms cause the most damage in total, while north-westerly windstorms individually lead to the highest average outages. The largest impacts occur when a windstorm moves across the northern part of the country, from the north-west to east, with the strongest wind gusts concentrated on the southern side of the low-pressure centre, in highly populated regions. Of the meteorological characteristics of windstorms, the most relevant for grid damage besides the wind gust speed are the extent and spatial distribution of wind gusts. The seasonal analysis shows that windstorms are more frequent and damaging in autumn and winter, but even weaker wind speeds during summer can cause significant damage. Factors such as soil frost influence the severity of windstorm damage, highlighting the importance of expanding research to include environmental and geographical aspects.

Numerous processes of neuronal development and synaptic plasticity in the brain rely on the palmitoyl acyltransferase ZDHHC7, as it palmitoylates various synaptic and extrasynaptic proteins such as neural cell adhesion molecule (NCAM) or gamma-aminobutyric acid (GABAA) receptors. In addition, ZDHHC7 palmitoylates sex steroid hormone receptors and is, therefore, indirectly linked to mental disorders that often occur because of or in conjunction with stress. In this work, we investigated how ZDHHC7 affects stress responses in mice. For this purpose, genetically modified mice with a knockout of the Zdhhc7 gene (KO) and wild-type (WT) littermates of both sexes were exposed to acute stressors or control conditions and examined with regard to their behavior, brain microstructure, gene expression, and synaptic plasticity. While no behavioral effects of acute stress were found, we did find that acute stress caused reduced mRNA levels of Esr1 and Esr2 coding for estrogen receptor α and β in the medial prefrontal cortex of male WT and KO mice. Strikingly, after acute stress only male KO mice showed reduced mean fiber lengths of the medioventral hippocampus. Furthermore, Zdhhc7-deficiency impaired synaptic plasticity in mice of both sexes, while acute stress improved it in females, but not in male mice. Taken together, our findings suggest that ZDHHC7 plays a modulatory role in the brain that leads to sex-specific stress responses, possibly due to estrogen receptor-mediated signaling pathways.

Adenosine, its interacting A and A receptors, and particularly the variant rs5751876 in the A gene ADORA2A have been shown to modulate anxiety, arousal, and sleep. In a pilot positron emission tomography (PET) study in healthy male subjects, we suggested an effect of rs5751876 on in vivo brain A receptor (A AR) availability. As female sex and adenosinergic/dopaminergic interaction partners might have an impact on this rs5751876 effect on A AR availability, we aimed to (1) further investigate the pilot male-based findings in an independent, newly recruited cohort including women and (2) analyze potential modulation of this rs5751876 effect by additional adenosinergic/dopaminergic gene variation. Healthy volunteers (32/11 males/females) underwent phenotypic characterization including self-reported sleep and A AR-specific quantitative PET. Rs5751876 and 31 gene variants of adenosine A , A , A , and A receptors, adenosine deaminase, and dopamine D receptor were genotyped. Multivariate analysis revealed an rs5751876 effect on A AR availability (P = 0.047), post hoc confirmed in 30 of 31 brain regions (false discovery rate (FDR) corrected P values < 0.05), but statistically stronger in anxiety-related regions (e.g., amygdala, hippocampus). Additional effects of ADORA1 rs1874142 were identified; under its influence rs5751876 and rs5751876 × sleep had strengthened effects on A AR availability (P  < 0.02; post hoc FDR-corrected Ps < 0.05 for 29/30 regions, respectively). Our results support the relationship between rs5751876 and A AR availability. Additional impact of rs1874142, together with rs5751876 and sleep, might be involved in regulating arousal and thus the development of mental disorders like anxiety disorders. The interplay of further detected suggestive ADORA2A × DRD2 interaction, however, necessitates larger future samples more comparable to magnetic resonance imaging (MRI)-based samples.

Background: Bio-logging and animal tracking datasets continuously grow in volume and complexity, documenting animal behaviour and ecology in unprecedented extent and detail, but greatly increasing the challenge of extracting knowledge from the data obtained. A large variety of analysis methods are being developed, many of which in effect are inaccessible to potential users, because they remain unpublished, depend on proprietary software or require significant coding skills. Results: We developed MoveApps, an open analysis platform for animal tracking data, to make sophisticated analytical tools accessible to a global community of movement ecologists and wildlife managers. As part of the Movebank ecosystem, MoveApps allows users to design and share workflows composed of analysis modules (Apps) that access and analyse tracking data. Users browse Apps, build workflows, customise parameters, execute analyses and access results through an intuitive web-based interface. Apps, coded in R or other programming languages, have been developed by the MoveApps team and can be contributed by anyone developing analysis code. They become available to all user of the platform. To allow long-term and cross-system reproducibility, Apps have public source code and are compiled and run in Docker containers that form the basis of a serverless cloud computing system. To support reproducible science and help contributors document and benefit from their efforts, workflows of Apps can be shared, published and archived with DOIs in the Movebank Data Repository. The platform was beta launched in spring 2021 and currently contains 44 Apps that are used by 156 registered users. We illustrate its use through two workflows that (1) provide a daily report on active tag deployments and (2) segment and map migratory movements. Conclusions: The MoveApps platform is meant to empower the community to supply, exchange and use analysis code in an intuitive environment that allows fast and traceable results and feedback. By bringing together analytical experts developing movement analysis methods and code with those in need of tools to explore, answer questions and inform decisions based on data they collect, we intend to increase the pace of knowledge generation and integration to match the huge growth rate in bio-logging data acquisition. Competing Interest Statement The authors have declared no competing interest.

A new technique termed spatially resolved matrix isolation spectroscopy was invented. Three separate methods for obtaining uv/visible absorption data with a diode array rapid scan spectrometer (DARSS) were developed. A monochromatic detection source illuminates a lateral strip across a cryogenic matrix in the first method. By exploiting the rigidity of the matrix, the spatially resolved spectra can be parametrically labeled by another experimental variable, such as photolysis wavelength from dispersed radiation. The linear array of diodes records changes in the absorption spectrum of the matrix before and after photolysis. Alternatively, full uv/visible absorption spectra of individual regions of the matrix can be recorded when the DARSS/monochromator system is operated in a scanning mode. The absolute thickness of a matrix can be measured by these individual channel or diode spectra, allowing determination of the concentration of absorbing species in the matrix. The third method of DARSS operation is a rapid multiplexing mode in which the visible spectrum of a spatially uniform sample can be recorded in (LESSTHEQ)1 s, a speed which is important for photochemically active samples. From spatially resolved spectra of the Cr(CO)(,6) photosystem in argon matrices, three visible absorption bands of the photochemical products have been assigned: 569 nm - Cr(CO)(,5); 515 and 415 nm - Cr(CO)(,4). Gaussian functions fitted to the DARSS spectra allowed the half widths of the bands and the extent of overlap to be estimated. Under the given photolysis conditions, typical full widths at half maxima were 182, 139 and 37 nm respectively. Both Cr(CO)(,5) and Cr(CO)(,4) were primary photolysis products at 313 nm uv irradiation. It was determined that a photolysis energy of 91 kcal/mol is thus sufficient to break two Cr-CO bonds and produce electronically excited Cr(CO)(,5) and Cr(CO)(,4) fragments. Unfiltered uv photolysis with a Hg arc source produces the same species, but Cr(CO)(,5) also undergoes secondary decomposition to produce more Cr(CO)(,4). The recombination of Cr(CO)(,4) and Cr(CO)(,5) with ejected CO fragments was observed at visible photolysis wavelengths. The feasibility of high spectral and spatial infrared detection using Fourier transform interferometric spectrometry was demonstrated with OCS/Ar matrices ((upsilon)(,1) band at 2049.6 cm('-1)).