Assessment of the risk of African swine fever introduction into Finland using NORA : a rapid tool for semiquantitative assessment of the risk

The NORA rapid risk assessment tool was developed for situations where there is a change in the disease status of easily transmissible animal diseases in neighbouring countries or in countries with significant interactions with Finland. The goal was to develop a tool that is quick to use and will provide consistent results to support risk management decisions. The model contains 63 questions that define the potential for entry and exposure by nine different pathways. The magnitude of the consequences is defined by 23 statements. The weight of different pathways is defined according to the properties of the assessed disease. The model was built as an Excel spreadsheet and is intended for use by animal health control administrators. As an outcome, the model gives the possible pathways of disease entry into the country, an overall approximation for the probability of entry and the subsequent exposure, an overall estimate for the consequences and a combined overall risk estimate (probability multiplied by magnitude of consequences). Model validity was assessed by expert panels. Outside Africa, African swine fever is currently established in Russia and Sardinia. In addition, there have been cases in both wild boar and domestic pigs in Latvia, Lithuania, Poland and Estonia. Finland has frequent contacts with Russia and Estonia, especially through passengers. The risk of African swine fever (ASF) introduction into Finland was tested with NORA for the situation in December 2015, when ASF was endemic in many parts of Russia, Africa and Sardinia and was present in Baltic countries and in Poland. African swine fever was assessed to have a high probability of entry into Finland, with high consequences and therefore a high overall risk

Automation aspects for the georeferencing of photogrammetric aerial image archives in forested scenes

Photogrammetric aerial film image archives are scanned into digital form in many countries. These data sets offer an interesting source of information for scientists from different disciplines. The objective of this investigation was to contribute to the automation of a generation of 3D environmental model time series when using small-scale airborne image archives, especially in forested scenes. Furthermore, we investigated the usability of dense digital surface models (DSMs) generated using these data sets as well as the uncertainty propagation of the DSMs. A key element in the automation is georeferencing. It is obvious that for images captured years apart, it is essential to find ground reference locations that have changed as little as possible. We studied a 68-year-long aerial image time series in a Finnish Karelian forestland. The quality of candidate ground locations was evaluated by comparing digital DSMs created from the images to an airborne laser scanning (ALS)-originated reference DSM. The quality statistics of DSMs were consistent with the expectations; the estimated median root mean squared error for height varied between 0.3 and 2 m, indicating a photogrammetric modelling error of 0.1 parts per thousand with respect to flying height for data sets collected since the 1980s, and 0.2 parts per thousand for older data sets. The results show that of the studied land cover classes, "peatland without trees" changed the least over time and is one of the most promising candidates to serve as a location for automatic ground control measurement. Our results also highlight some potential challenges in the process as well as possible solutions. Our results indicate that using modern photogrammetric techniques, it is possible to reconstruct 3D environmental model time series using photogrammetric image archives in a highly automated way.Peer reviewe

Progress towards high efficiency thin-film III-V quantum dot solar cells for space

This work summarizes our results in the development of high efficiency III-V quantum dot (QD) solar cells, aimed at tackling with two of the most relevant issues posed by QD solar cells (QDSCs), namely the degradation of open circuit voltage and the weak photon harvesting by QDs. In particular, we report our latest achievements in: i) The molecular beam epitaxy growth of high-quality QDSCs, demonstrating Voc as high as 0.94 V and low penalty (~ 40 mV) with respect to the single-junction reference cell. ii) The development by nanoimprint lithography of metal/polymer back reflectors with high diffraction efficiency, enabling four times increase of the QD photogenerated current. Experimental results are discussed with the support of numerical simulations

Genetic differential susceptibility to the parent-child relationship quality and the life span development of compassion

The development of compassion for others might be influenced by the social experiences made during childhood and has a genetic component. No research has yet investigated whether the parent-child relationship quality interacts with genetic variation in the oxytocin and dopamine systems in predicting compassion over the life span. In the prospective Young Finns Study (N = 2099, 43.9% men), we examined the interaction between mother-reported emotional warmth and intolerance toward their child assessed in 1980 (age of participants, 3-18 years) and two established genetic risk scores for oxytocin levels and dopamine signaling activity. Dispositional compassion for others was measured with the Temperament and Character Inventory 1997, 2001, and 2012 (age of participants, 20-50 years). We found a gene-environment interaction (p = .031) that remained marginally significant after adjustment for multiple testing. In line with the differential susceptibility hypothesis, only participants who carry alleles associated with low dopamine signaling activity had higher levels of compassion when growing up with emotionally warm parents, whereas they had lower levels of compassion when their parents were emotionally cold. Children's genetic variability in the dopamine system might result in plasticity to early environmental influences that have a long-lasting effect on the development of compassion. However, our findings need replication.Peer reviewe

Genome-wide association meta-analysis of corneal curvature identifies novel loci and shared genetic influences across axial length and refractive error

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Uncovering the complex genetic architecture of human plasma lipidome using machine learning methods

Genetic architecture of plasma lipidome provides insights into regulation of lipid metabolism and related diseases. We applied an unsupervised machine learning method, PGMRA, to discover phenotype-genotype many-to-many relations between genotype and plasma lipidome (phenotype) in order to identify the genetic architecture of plasma lipidome profiled from 1,426 Finnish individuals aged 30-45 years. PGMRA involves biclustering genotype and lipidome data independently followed by their inter-domain integration based on hypergeometric tests of the number of shared individuals. Pathway enrichment analysis was performed on the SNP sets to identify their associated biological processes. We identified 93 statistically significant (hypergeometric p-value \u3c 0.01) lipidome-genotype relations. Genotype biclusters in these 93 relations contained 5977 SNPs across 3164 genes. Twenty nine of the 93 relations contained genotype biclusters with more than 50% unique SNPs and participants, thus representing most distinct subgroups. We identified 30 significantly enriched biological processes among the SNPs involved in 21 of these 29 most distinct genotype-lipidome subgroups through which the identified genetic variants can influence and regulate plasma lipid related metabolism and profiles. This study identified 29 distinct genotype-lipidome subgroups in the studied Finnish population that may have distinct disease trajectories and therefore could be useful in precision medicine research

Genetic predisposition to adiposity is associated with increased objectively assessed sedentary time in young children.

Increased sedentariness has been linked to the growing prevalence of obesity in children, but some longitudinal studies suggest that sedentariness may be a consequence rather than a cause of increased adiposity. We used Mendelian randomization to examine the causal relations between body mass index (BMI) and objectively assessed sedentary time and physical activity in 3-8 year-old children from one Finnish and two Danish cohorts [NTOTAL=679]. A genetic risk score (GRS) comprised of 15 independent genetic variants associated with childhood BMI was used as the instrumental variable to test causal effects of BMI on sedentary time, total physical activity, and moderate-to-vigorous physical activity (MVPA). In fixed effects meta-analyses, the GRS was associated with 0.05 SD/allele increase in sedentary time (P=0.019), but there was no significant association with total physical activity (beta=0.011 SD/allele, P=0.58) or MVPA (beta=0.001 SD/allele, P=0.96), adjusting for age, sex, monitor wear-time and first three genome-wide principal components. In two-stage least squares regression analyses, each genetically instrumented one unit increase in BMI z-score increased sedentary time by 0.47 SD (P=0.072). Childhood BMI may have a causal influence on sedentary time but not on total physical activity or MVPA in young children. Our results provide important insights into the regulation of movement behaviour in childhood