Geographical patterns in the radial growth response of Norway spruce provenances to climatic variation

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Real-time human detection from depth images with heuristic approach

Abstract. The first industrial robot was built in the mid-20th century. The idea of the industrial robots was to replace humans in assembly lines, where the tasks were repetitive and easy to do. The benefits of these robots are that they are able to work around the clock and only need electricity as compensation. Over the years, robots capable of only doing repetitive tasks have evolved to operate fully autonomously in challenging environments. Some examples of these are self-driving cars and service robots that can work as customer servants. This is mainly accomplished through advancements in artificial intelligence, machine vision, and depth camera technologies. With machine vision and depth perception, robots are able to construct a fully structured environment around them and this allows them to properly react to sudden changes in their surroundings. In this project, a naive detection algorithm was implemented to separate humans from depth images. The algorithm works by removing the ground plane, after which the floating objects can be separated more easily. The floating objects are further processed, and the human detection part is then achieved using a heuristic approach. The proposed algorithm works in real time and reliably detects people standing in a relatively open environment. However, because of the naive approach, human-sized items are wrongly detected as humans in some scenarios.Tiivistelmä. Ensimmäinen teollisuusrobotti rakennettiin 1900-luvun puolivälissä. Teollisuusrobottien tarkoitus oli korvata ihmiset tehtaiden kokoonpanolinjoilla, joissa työtehtävät olivat pääsääntöisesti yksinkertaisia ja itseään toistavia. Näiden robottien etuna on, että ne kykenevät työskentelemään kellon ympäri pelkän sähkön varassa. Vuosien mittaan robotit ovat kehittyneet yksinkertaisista koneista roboteiksi, jotka kykenevät toimimaan täysin itsenäisesti haastavissakin olosuhteissa. Itseajavat autot ja asiakaspalvelijana toimivat palvelurobotit ovat näistä hyviä esimerkkejä. Tällaiset saavutukset ovat olleet mahdollisia tekoälyn, konenäön ja syvyyskameroiden kehityksen myötä. Kone- ja syvyysnäön avulla robotit pystyvät muodostamaan itselleen selkeän kuvan ympäristöstään, mikä mahdollistaa nopean reagoinnin yllättäviinkin muutoksiin ympäristössä. Tässä työssä toteutettiin naiivi havaitsemisalgoritmi erottelemaan ihmiset syvyyskuvista. Algoritmi poistaa maatason, jonka jälkeen ilmassa leijuvat esineet voidaan erotella toisistaan. Erotetut esineet jatkokäsitellään, jonka jälkeen ihmisten havaitseminen toteutetaan heuristisella menetelmällä. Työssä esitelty algoritmi toimii reaaliajassa ja pystyy luotettavasti havaitsemaan ihmiset suhteellisen avoimessa ympäristössä, vaikkakin joissain tapauksissa ihmisen kokoiset esineet luokitellaan väärin ihmisiksi naiivin lähestymistavan vuoksi

Evaluation of Innotrac Aio! Second-Generation Cardiac Troponin I Assay: The Main Characteristics for Routine Clinical Use

The availability of a simple, sensitive, and rapid test using whole blood to facilitate processing and to reduce the turnaround time could improve the management of patients presenting with chest pain. The aim of this study was an evaluation of the Innotrac Aio! second-generation cardiac troponin I (cTnI) assay. The Innotrac Aio! second-generation cTnI assay was compared with the Abbott AxSYM first-generation cTnI, Beckman Access AccuTnI, and Innotrac Aio! first-generation cTnI assays. We studied serum samples from 15 patients with positive rheumatoid factor but with no indication of myocardial infarction (MI). Additionally, the stability of the sample with different matrices and the influence of hemodialysis on the cTnI concentration were evaluated. Within-assay CVs were 3.2%–10.9%, and between-assay precision ranged from 4.0% to 17.2% for cTnI. The functional sensitivity (CV = 20 %) and the concentration giving CV of 10% were approximated to be 0.02 and 0.04, respectively. The assay was found to be linear within the tested range of 0.063–111.6 μ g/L. The correlations between the second-generation Innotrac Aio!, Access, and AxSYM cTnI assays were good (r coefficients 0.947–0.966), but involved differences in the measured concentrations, and the biases were highest with cTnI at low concentrations. The second-generation Innotrac Aio! cTnI assay was found to be superior to the first-generation assay with regard to precision in the low concentration range. The stability of the cTnI level was best in the serum, lithium-heparin plasma, and lithium-heparin whole blood samples (n = 10 , decrease < 10 % in 24 hours at +20°C and at +4°C. There was no remarkable influence of hemodialysis on the cTnI release. False-positive cTnI values occurred in the presence of very high rheumatoid factor values, that is, over 3000 U/L. The 99th percentile of the apparently healthy reference group was ≤ 0.03   μ g/L. The results demonstrate the very good analytical performance of the second-generation Innotrac Aio! cTnI assay

Connecting potential frost damage events identified from meteorological records to radial growth variation in Norway spruce and Scots pine

The aim of this study was to examine if temperature conditions potentially causing frost damage have an effect on radial growth in Norway spruce and Scots pine in Finland. We hypothesized that frost damage occurs and reduces radial growth after (1) extreme cold winter temperatures, (2) frost hardiness levels insufficient to minimum temperatures, and (3) the lack of insulating snow cover during freezing temperatures, resulting in increased frost and decreased temperatures in soil. Meteorological records were used to define variables describing the conditions of each hypothesis and a dynamic frost hardiness model was used to find events of insufficient frost hardiness levels. As frost damage is likely to occur only under exceptional conditions, we used generalized extreme value distributions to describe the frost variables. Our results did not show strong connections between radial growth and the frost damage events. However, significant growth reductions were found at some Norway spruce sites after events insufficient frost hardiness levels, and alternatively, after winters with high frost sum of snowless days. Scots pine did not show significant growth reductions associated with any of the studied variables. Thus, radial growth in Norway spruce may be more sensitive to future changes in winter conditions. Our results demonstrate that considering only temperature is unlikely to be sufficient in studying winter temperature effects on tree growth. Instead, understanding the effects of changing temperature and snow conditions in relation to tree physiology and phenology is needed.201

A novel negevirus isolated from Aedes vexans mosquitoes in Finland

Negeviruses are insect-specific enveloped RNA viruses that have been detected in mosquitoes and sandflies from various geographical locations. Here, we describe a new negevirus from Northern Europe, isolated from pool ofAedes vexansmosquitoes collected in Finland, designated as Mekrijarvi negevirus (MEJNV). MEJNV had a typical negevirus genome organization, is 9,740 nucleotides in length, and has a GC content of 47.53%. The MEJNV genome contains three ORFs, each containing the following identified conserved domains: ORF1 (7,068 nt) encodes a viral methyltransferase, an FtsJ-like methyltransferase, a viral RNA helicase, and an RNA-dependent RNA polymerase, ORF2 (1,242 nt) encodes a putative virion glycoprotein, and ORF3 (660 nt) encodes a putative virion membrane protein. A distinctive feature relative to other currently known negeviruses is a 7-nucleotide-long overlap between ORF1 and ORF2. MEJNV shares the highest sequence identity with Ying Kou virus from China, with 67.71% nucleotide and 75.19% and 59.00% amino acid sequence identity in ORF 1 and ORF 2, respectively. ORF3 had the highest amino acid sequence similarity to Daeseongdong virus 1 and negevirus Nona 1, both with 77.61% identity, and to Ying Kou virus, with 71.22% identity. MEJNV is currently the northernmost negevirus described. Our report supports the view that negeviruses are a globally distributed, diverse group of viruses that can be found from mosquitoes in a wide range of terrestrial biomes from tropical to boreal forests.Peer reviewe

Sindbis Virus Strains of Divergent Origin Isolated from Humans and Mosquitoes During a Recent Outbreak in Finland

Sindbis virus (SINV) is a mosquito-borne avian hosted virus that is widely distributed in Europe, Africa, Asia, and Oceania. Disease in humans is documented mainly from Northern Europe and South Africa and associated with genotype I. In 2018 under extremely warm climatic conditions, a small outbreak of 71 diagnosed SINV infections was recorded in Finland. We screened 52 mosquito pools (570 mosquitoes) and 223 human sera for SINV with real-time RT-PCR and the positive samples with virus isolation. One SINV strain was isolated from a pool (n = 13) of genusOchlerotatusmosquitoes and three strains from patient serum samples. Complete genome analysis suggested all the isolates to be divergent from one another and related to previous Finnish, Swedish, and German strains. The study provides evidence of SINV strain transfer within Europe across regions with different epidemiological characteristics. Whether these are influenced by different mosquito genera involved in the transmission remains to be studied.Peer reviewe

High-resolution topographical information improves tree-level storm damage models

Storms cause major forest disturbances in Europe. The aim of this study was to model tree-level storm damage probability based on the properties of a tree and its environment and to examine whether fine-scale topographic information is connected to the damage probability. We used data documenting effects of two autumn storms on over 17 000 trees on permanent Finnish National Forest Inventory plots. The first storm was associated with wet snowfall that damaged trees, while exceptionally strong winds and gusts characterized the second storm. During the storms, soils were unfrozen and deciduous trees were without leaves. Generalized linear mixed models were used to study how topographical variables calculated from digital elevation models (DEM) with resolutions of 2 and 10 m (TOPO2 and TOPO10, respectively) were related to damage probability, in addition to variable groups for tree (TREE) and stand (STAND) characteristics. We compared models containing different variable groups with Akaike information criteria. The best model contained the variable groups TREE, STAND, and TOPO2. Increase in slope steepness calculated from the high-resolution DEM decreased tree-level damage probability significantly in the model. This suggests that the local topography affects the tree-level damage probability and that high-resolution topographical data improves the tree-level damage probability models.Peer reviewe

Characterisation of the RNA Virome of Nine Ochlerotatus Species in Finland

RNA viromes of nine commonly encountered Ochlerotatus mosquito species collected around Finland in 2015 and 2017 were studied using next-generation sequencing. Mosquito homogenates were sequenced from 91 pools comprising 16–60 morphologically identified adult females of Oc. cantans, Oc. caspius, Oc. communis, Oc. diantaeus, Oc. excrucians, Oc. hexodontus, Oc. intrudens, Oc. pullatus and Oc. punctor/punctodes. In total 514 viral Reverse dependent RNA polymerase (RdRp) sequences of 159 virus species were recovered, belonging to 25 families or equivalent rank, as follows: Aliusviridae, Aspiviridae, Botybirnavirus, Chrysoviridae, Chuviridae, Endornaviridae, Flaviviridae, Iflaviridae, Negevirus, Partitiviridae, Permutotetraviridae, Phasmaviridae, Phenuiviridae, Picornaviridae, Qinviridae, Quenyavirus, Rhabdoviridae, Sedoreoviridae, Solemoviridae, Spinareoviridae, Togaviridae, Totiviridae, Virgaviridae, Xinmoviridae and Yueviridae. Of these, 147 are tentatively novel viruses. One sequence of Sindbis virus, which causes Pogosta disease in humans, was detected from Oc. communis from Pohjois-Karjala. This study greatly increases the number of mosquito-associated viruses known from Finland and presents the northern-most mosquito-associated viruses in Europe to date

An interpretable method for automated classification of spoken transcripts and written text

We investigate the differences between spoken language (in the form of radio show transcripts) and written language (Wikipedia articles) in the context of text classification. We present a novel, interpretable method for text classification, involving a linear classifier using a large set of n- gram features, and apply it to a newly generated data set with sentences originating either from spoken transcripts or written text. Our classifier reaches an accuracy less than 0.02 below that of a commonly used classifier (DistilBERT) based on deep neural networks (DNNs). Moreover, our classifier has an integrated measure of confidence, for assessing the reliability of a given classification. An online tool is provided for demonstrating our classifier, particularly its interpretable nature, which is a crucial feature in classification tasks involving high-stakes decision-making. We also study the capability of DistilBERT to carry out fill-in-the-blank tasks in either spoken or written text, and find it to perform similarly in both cases. Our main conclusion is that, with careful improvements, the performance gap between classical methods and DNN-based methods may be reduced significantly, such that the choice of classification method comes down to the need (if any) for interpretability