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

Barrier, converting, and tray-forming properties of paperboard packaging materials coated with waterborne dispersions

In this work, different food-contact experimental and commercial aqueous polymeric dispersions were applied to paperboard via rod coating technology to achieve <5% non-cellulosic content. Barrier (water, moisture and grease), mechanical (tensile and bending) and converting (heat-sealing and creasing) properties were analysed before tray formation trials on pilot-scale equipment. Dispersion-coated samples were compared against polyethylene terephthalate (PET) extrusion-coated paperboard, the principal industrial material used for food trays. Results show that, within the investigated properties, waterborne dispersions can achieve similar barrier properties compared with PET, yet at lower dry coat grammage (12 g/m(2) vs. 40 g/m(2 )of PET-coated paperboard). Additionally, the investigated coatings heat-sealed at temperatures as low as 80-90(degrees)C, almost 100(degrees)C less than PET; however, lower seal forces could be achieved (15-20 N/(25 mm) vs. 23 N/(25 mm) of PET-coated paperboard). Paperboard delamination occurred at the highest seal forces. Dispersion-coated trays were obtained at 4.5-5.0% blank moisture content. Formed trays at industrial processing parameters showed critical coating damage during converting due to tensile stresses. This work shows that milder processing conditions allow a reduction in coat defects

Sars - uusiin uhkiin valmistautumista

Kansainvälisen sars-epidemian aiheuttama toiminta Suomessa antoi arvokasta kokemusta odottamattomien tartuntatautiuhkien torjumiseen ja korosti varautumisen merkitystä. Uusien tutkimustietojen tulkinta, niiden käytäntöön soveltaminen, suositusten ja ohjeiden päivittäminen sekä viestintä yleisölle olivat suuri haaste viranomaisille. Avainasemassa ovat tapausten varhainen tunnistaminen torjuntatoimien käynnistämiseksi, tehokas koordinaatio terveydenhuollon organisaatioiden kesken, hyvä eri hallinnonalojen organisaatioiden välinen yhteistyö ja tiedottaminen. Tartuntatautien käytettävissä olevat resurssit ovat riittämättömiä laajan, äkillisen epidemian torjuntaan ja niitä tulisi selvästi vahvistaa olemassa olevissa organisaatioissa

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

The reliability of the McCabe score as a marker of co-morbidity in healthcare-associated infection point prevalence studies

This study aimed to ascertain the reliability of the McCabe score in a healthcare-associated infection point prevalence survey.   A 10 European Union Member States survey in 20 hospitals (n = 1912) indicated that there was a moderate level of agreement (κ = 0.57) with the score. The reliability of the application of the score could be increased by training data collectors, particularly with reference to the ultimately fatal criteria. This is important if the score is to be used to risk adjust data to drive infection prevention and control interventions

The potential of dual-wavelength terrestrial lidar in early detection of Ips typographus (L.) infestation – Leaf water content as a proxy

Climate change is causing novel forest stress around the world due to changes in environmental conditions. Forest pest insects, such as Ips typographus (L.), are spreading toward the northern latitudes and are now able to produce more generations in their current range; this has increased forest disturbances. Timely information on tree decline is critical in allowing forest managers to plan effective countermeasures and to forecast potential infestation areas. Field-based infestation surveys of bark beetles have traditionally involved visual estimates of entrance holes, resin flow, and maternal-gallery densities; such estimates are prone to error and bias. Thus, objective and automated methods for estimating tree infestation status are required.In this study, we investigated the feasibility of dual-wavelength terrestrial lidar in the estimation and detection of I. typographus infestation symptoms. In addition, we examined the relationship between leaf water content (measured as gravimetric water content and equivalent water thickness) and infestation severity. Using two terrestrial lidar systems (operating at 905 nm and 1550 nm), we measured 29 mature Norway spruce (Picea abies [L.] Karst.) trees that exhibited low or moderate infestation symptoms. We calculated single and dual-wavelength lidar intensity metrics from stem and crown points to test these metrics' ability to discriminate I. typographus infestation levels using regressions and linear discriminant analyses.Across the various I. typographus infestation levels, we found significant differences (p </p

The potential of dual-wavelength terrestrial lidar in early detection of Ips typographus (L.) infestation – Leaf water content as a proxy

Climate change is causing novel forest stress around the world due to changes in environmental conditions. Forest pest insects, such as Ips typographus (L.), are spreading toward the northern latitudes and are now able to produce more generations in their current range; this has increased forest disturbances. Timely information on tree decline is critical in allowing forest managers to plan effective countermeasures and to forecast potential infestation areas. Field-based infestation surveys of bark beetles have traditionally involved visual estimates of entrance holes, resin flow, and maternal-gallery densities; such estimates are prone to error and bias. Thus, objective and automated methods for estimating tree infestation status are required. In this study, we investigated the feasibility of dual-wavelength terrestrial lidar in the estimation and detection of I. typographus infestation symptoms. In addition, we examined the relationship between leaf water content (measured as gravimetric water content and equivalent water thickness) and infestation severity. Using two terrestrial lidar systems (operating at 905 nm and 1550 nm), we measured 29 mature Norway spruce (Picea abies [L.] Karst.) trees that exhibited low or moderate infestation symptoms. We calculated single and dual-wavelength lidar intensity metrics from stem and crown points to test these metrics' ability to discriminate I. typographus infestation levels using regressions and linear discriminant analyses. Across the various I. typographus infestation levels, we found significant differences (p Peer reviewe